CN112191537A - Logistics package sorting system based on artificial intelligence - Google Patents
Logistics package sorting system based on artificial intelligence Download PDFInfo
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- CN112191537A CN112191537A CN202011128782.9A CN202011128782A CN112191537A CN 112191537 A CN112191537 A CN 112191537A CN 202011128782 A CN202011128782 A CN 202011128782A CN 112191537 A CN112191537 A CN 112191537A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C3/00—Sorting according to destination
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Abstract
The invention relates to a logistics package sorting system based on artificial intelligence, which comprises a planning and scheduling unit, a real-time optimization control unit, a fault diagnosis unit, a local control unit and an execution unit, wherein the planning and scheduling unit is used for carrying out real-time optimization control on the logistics package sorting system; the plan scheduling unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the plan scheduling unit, the fault diagnosis unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the execution unit, and the local control unit is connected with the execution unit; through the plan scheduling unit of the logistics package sorting system based on artificial intelligence, logistics enterprises can complete order tasks on time under the condition of saving a large amount of manpower and equipment resources, and through the fault diagnosis unit and the real-time optimization control unit of the system, the logistics enterprises can complete orders on time quickly and cost-effectively under the condition of equipment fault and maintenance.
Description
Technical Field
The invention relates to the technical field of logistics sorting, in particular to a logistics package sorting system based on artificial intelligence.
Background
With the change of demand patterns of modern society, logistics serves as a 'third profit source', and the logistics becomes an industry in China. However, as the logistics operation environment changes, the operation demand is increased, the traditional operation mode cannot meet the requirement of the logistics service function, taking the picking operation of the distribution center as an example, under the condition that the operation personnel, the operation object, the operation position and the like are continuously and dynamically changed, the operation scheduling difficulty is increased, the operation flexibility of the picking system is not strong, the overall benefit is not good, and in order to meet the requirement of the operation function, a new operation mode needs to be introduced to enhance the adaptability of the system.
At present, most distribution centers in China still belong to labor-intensive operation, wherein the sorting operation occupies most resources, so the sorting operation is one of important activities of the distribution centers. And the sorting operation not only affects the logistics cost, but also has important influence on the delivery time, accuracy and the like required by customers. The design and management planning of sorting systems is made increasingly important.
Although the logistics industry in China starts late, the sorting operation is still in a development stage, and the proportion of manual operation in the sorting system is high, the mechanical, automatic and intelligent sorting system is the main characteristic and development trend of the modern sorting system.
Many domestic logistics distribution centers also begin to combine their own features and use high technology content equipment and systems to improve sorting distribution efficiency. For example: the storage system combining a high-rise three-dimensional goods shelf and a disassembled goods sorting goods shelf, a forward-moving type storage battery forklift, an electric carrier, an electric sorting truck and a tray are adopted, so that the loading, unloading and carrying operation is mechanized, and the disassembled goods distribution is electronized; the electronic tag sorting system and the electronic tag equipment are adopted, so that the sorting operation speed is greatly improved, and the goods sorting error rate is reduced; automatic sorting techniques, etc.
CN106997517A the present disclosure discloses a logistics distribution method, comprising the following steps: when the fourth logistics is delivered, the consignee address corresponding to one or more packages is converted into an address identifier corresponding to the consignee address according to a pre-stored address library and a preset address conversion rule; a fourth party logistics sends the address identification to one or more carriers for logistics distribution of one or more packages. The logistics distribution method can convert the address of the receiver into the address identification corresponding to the address of the receiver, quickly mark the address, is suitable for international logistics distribution, eliminates language gap, facilitates distribution, effectively improves logistics distribution efficiency, reduces distribution cost, and further reduces the problems of package loss and the like caused by unpacking while improving distribution efficiency. The disclosure also discloses a logistics distribution system and a fourth logistics system.
The invention discloses a CN109013356A logistics sorting system, and belongs to the technical field of logistics sorting. The logistics sorting system comprises an electric tray, a main line track, a blanking grid and an electric control cabinet; the intelligent camera is arranged in a bracket crossing over the main line track, photographs the electric tray and the packages in the electric tray, and judges the distance between the packages and the blanking edge of the electric tray; the industrial computer controls the electric tray through the wireless connection of the communication unit and the electric tray in the electric control cabinet, so that the packages in the electric tray move towards the direction of the specified blanking grid opening. Can make electronic tray like this when carrying along the thread track, can move the tray edge of appointed unloading check mouth direction one side with the parcel in advance, be convenient for the quick unloading of parcel when electronic tray moves appointed unloading check mouth to improve letter sorting efficiency, reduce the letter sorting mistake.
CN109107907A the present application provides a method for sorting articles, comprising: determining a target sorting layer in a multi-layer sorting device and a target sorting port on the target sorting layer for an article to be sorted; determining a mobile transport device for the item to be sorted; determining a target transport path for the mobile transport device to reach a target sorting gate of the target sorting level; and controlling the mobile conveyer to convey the to-be-sorted articles to the target sorting opening of the target sorting layer along the target conveying path. The application also provides an article sorting device, an article sorting system and a multilayer sorting device. Adopt this application embodiment, can carry out more efficient letter sorting to the commodity circulation parcel, still make setting up of multilayer sorting device can further improve article letter sorting efficiency to, the removal of control robot etc. all have special article sorting device to accomplish, can not influence each other between each layer robot, have also guaranteed going on smoothly high-efficiently of article letter sorting.
CN111282830A the embodiment of the present application discloses a conveying device, a control method, and a device, wherein the conveying device specifically includes: a body; and a plurality of tray devices horizontally arranged on the body, wherein the tray devices can move in a vertical direction so as to enable the tray devices to bear or move the logistics objects at the corresponding first positions. The embodiment of the application can utilize less conveying equipment to sort the same packages; meanwhile, the number of conveying equipment in the logistics field can be reduced, and the smoothness of traffic conditions in the logistics field is improved; and the sorting efficiency of the packages can be improved because useless return paths can be reduced.
The existing patent documents do not consider how to carry out resource allocation of the system to achieve the purposes of saving cost and quickly completing orders on time; the prior art does not consider how the system can not only save cost but also quickly complete orders on time in the state of equipment failure and maintenance. The patent gives the following solutions to the above problems.
Disclosure of Invention
The invention mainly aims to overcome the defects of the prior art and provides a logistics package sorting system based on artificial intelligence, which comprises a planning and scheduling unit, a real-time optimization control unit, a fault diagnosis unit, a local control unit and an execution unit; the plan scheduling unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the plan scheduling unit, the fault diagnosis unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the execution unit, and the local control unit is connected with the execution unit;
the execution unit comprises an identification device, a classification device, a conveying port, a conveying device and a sorting port; the identification device is arranged on the conveying opening, the conveying opening is connected with the conveying device, the classification device is arranged on the conveying device, and the sorting opening is connected with the conveying device;
the planning and scheduling unit is multi-objective optimization, wherein the objectives are minimization of sorting time and minimization of required resources under constraint conditions, the sorting time is a function of the required number of people, the number of delivery openings, the speed of the identification device, the speed of the classification device and the speed of the delivery device, and the required resources are a function of the required number of people, the number of delivery openings, the speed of the identification device, the speed of the classification device and the speed of the delivery device; obtaining optimal values of the required personnel number, the conveying port number, the speed of the identification device, the speed of the classification device and the speed of the conveying device by solving two goals of minimizing the required resources and the sorting time;
the real-time optimization control unit is used for real-time optimization control, the optimal value of the speed of the conveying device, which is given by the plan scheduling unit, is used as an initial set value, a process set value of the speed of the conveying device is given according to the speed of the identification device and the speed of the classification device, and the set value is sent to the local control unit.
The fault diagnosis unit comprises a fault diagnosis analysis module and fault diagnosis sensors, and the fault diagnosis sensors are arranged on the identification device, the classification device and the conveying device and respectively measure data; the error diagnosis sensor transmits the measurement data to the error diagnosis analysis module, which preferably analyzes the error states of the identification device, the classification device, and the transport device based on the measurement data.
Preferably, the failure diagnosis unit gives the upper limit value of the speed of the recognition device, the upper limit value of the speed of the classification device, and the upper limit value of the conveying speed of the conveying device, based on analysis of failure states of the recognition device, the classification device, and the conveying device.
Preferably, the failure diagnosis unit sends the speed upper limit value of the identification device, the speed upper limit value of the classification device, and the upper limit value of the conveying speed of the conveying device to the schedule scheduling unit in a cycle of 1 to 3 days.
Preferably, the fault diagnosis unit sends the real-time upper limit speed of the identification device, the real-time upper limit speed of the classification device, and the upper limit speed of the conveying device to the real-time optimization control unit in a period of 1-3 hours.
Preferably, the constraint conditions are that the number of required persons is less than an upper limit of persons, the number of conveying openings is less than an upper limit of the number of conveying openings, the speed of the identification device is less than an upper limit of speed, the speed of the classification device is less than an upper limit of speed, and the speed of the conveying device is less than an upper limit of speed.
Preferably, the scheduling unit sends the optimal values of the speed of the identification device, the speed of the classification device and the speed of the conveying device to the real-time optimization control unit, and the real-time optimization control unit sends the optimal values as initial values of set values to the local control unit.
Preferably, the real-time optimization control unit provides a process set value of the speed of the conveying device according to the real-time speed upper limit value of the identification device and the real-time speed upper limit value of the classification device, which are sent by the fault diagnosis unit, and sends the process set value to the local control unit.
Preferably, the identification device is in communication connection with the local control unit and sends the package information to the local control unit; the local control unit is connected with the classification device through a digital IO and controls the classification device through package information.
Preferably, the conveying device is connected with the local control unit through digital IO to control starting and stopping of the conveying device, and the conveying device is connected with the local control unit through analog IO to control the speed of the conveying device.
Has the advantages that: according to the logistics package sorting system based on artificial intelligence, disclosed by the invention, through the plan scheduling unit of the logistics package sorting system based on artificial intelligence, a logistics enterprise can complete order tasks on time under the condition of saving a large amount of manpower and equipment resources, and through the fault diagnosis unit and the real-time optimization control unit of the logistics package sorting system based on artificial intelligence, the logistics enterprise can complete orders on time quickly and at the condition of equipment fault and maintenance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a logistics parcel sorting system based on artificial intelligence;
in the figure: 1-a planning and scheduling unit, 2-a real-time optimization control unit, 3-a fault diagnosis unit, 4-a local control unit, 5-an execution unit,
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
As shown in fig. 1, a logistics package sorting system based on artificial intelligence comprises a planning and scheduling unit 1, a real-time optimization control unit 2, a fault diagnosis unit 3, a local control unit 4 and an execution unit 5; the scheduling unit 1 is connected with the real-time optimization control unit 2, the fault diagnosis unit 3 is connected with the scheduling unit 1, the fault diagnosis unit 3 is connected with the real-time optimization control unit 2, the fault diagnosis unit 3 is connected with the execution unit 5, and the local control unit 4 is connected with the execution unit 5.
The execution unit 5 comprises a recognition device 51, a classification device 52, a conveying port 53, a conveying device 54 and a sorting port 55; the identification device 51 is arranged on the conveying opening 53, the conveying opening 53 is connected with the conveying device 54, the classification device 52 is arranged on the conveying device 54, and the sorting channel opening 55 is connected with the conveying device 54.
The fault diagnosis unit 3 comprises a fault diagnosis analysis module and fault diagnosis sensors, wherein the fault diagnosis sensors are arranged on the identification device, the classification device and the conveying device and respectively measure data; and the fault diagnosis sensor sends the measurement data to the fault diagnosis analysis module, and the fault diagnosis analysis module adopts a neural network and a support vector machine intelligent algorithm and analyzes the fault states of the identification device, the classification device and the conveying device according to the measurement data. The failure diagnosis unit 3 gives the upper limit value of the speed of the recognition device, the upper limit value of the speed of the classification device, and the upper limit value of the conveying speed of the conveying device based on the analysis of the failure states of the recognition device, the classification device, and the conveying device. The failure diagnosis unit 3 sends the upper limit speed value of the identification device, the upper limit speed value of the classification device, and the upper limit conveying speed value of the conveying device to the schedule scheduling unit 1 in a cycle of 1 day. The fault diagnosis unit 3 sends the real-time speed upper limit value of the identification device, the real-time speed upper limit value of the classification device, and the upper limit value of the conveying speed of the conveying device to the real-time optimization control unit 2 in a period of 1 hour.
The planning and scheduling unit 1 is a multi-objective optimization, wherein the objectives are the minimization of sorting time and the minimization of required resources under constraint conditions, the sorting time is a function of the required number of people, the number of delivery openings, the speed of an identification device, the speed of a classification device and the speed of a delivery device, and the required resources are a function of the required number of people, the number of delivery openings, the speed of an identification device, the speed of a classification device and the speed of a delivery device; and solving two targets of minimizing the required resources and the sorting time by using ant colony, particle swarm and other swarm intelligent algorithms to obtain the optimal values of the required personnel number, the conveying port number, the speed of the identification device, the speed of the classification device and the speed of the conveying device. The constraint conditions are that the number of required personnel is smaller than an upper limit value of personnel, the number of the conveying openings is smaller than an upper limit value of the number of the conveying openings, the speed of the identification device is smaller than an upper limit value of speed, the speed of the classification device is smaller than the upper limit value of speed, and the speed of the conveying device is smaller than the upper limit value of speed.
The real-time optimization control unit 2 is used for real-time optimization control, the plan scheduling unit 1 sends the optimal values of the speed of the identification device, the speed of the classification device and the speed of the conveying device to the real-time optimization control unit 2, the real-time optimization control unit 2 calculates the optimal values by using a model prediction control algorithm based on a neural network, and the optimal values are used as initial values of set values and sent to the local control unit 4; according to the real-time speed upper limit value of the identification device and the real-time speed upper limit value of the classification device, which are sent by the fault diagnosis unit 3, the real-time optimization control unit 2 gives a process set value of the speed of the conveying device, and sends the process set value to the local control unit 4.
The identification device 51 is in communication connection with the local control unit 4 and sends package information to the local control unit 4; the local control unit 4 is connected to the sorting apparatus 52 through a digital IO, and controls the sorting apparatus 52 through package information. The digital IO connection between the conveying device 54 and the local control unit 4 controls the start and stop of the conveying device 54, and the analog IO connection between the conveying device 54 and the local control unit 4 controls the speed of the conveying device 54.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (10)
1. A logistics parcel sorting system based on artificial intelligence is characterized by comprising a planning and scheduling unit, a real-time optimization control unit, a fault diagnosis unit, a local control unit and an execution unit; the plan scheduling unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the plan scheduling unit, the fault diagnosis unit is connected with the real-time optimization control unit, the fault diagnosis unit is connected with the execution unit, and the local control unit is connected with the execution unit;
the execution unit comprises an identification device, a classification device, a conveying port, a conveying device and a sorting port; the identification device is arranged on the conveying opening, the conveying opening is connected with the conveying device, the classification device is arranged on the conveying device, and the sorting opening is connected with the conveying device;
the planning and scheduling unit is multi-objective optimization, wherein the objectives are minimization of sorting time and minimization of required resources under constraint conditions, the sorting time is a function of the required number of people, the number of delivery openings, the speed of the identification device, the speed of the classification device and the speed of the delivery device, and the required resources are a function of the required number of people, the number of delivery openings, the speed of the identification device, the speed of the classification device and the speed of the delivery device; obtaining optimal values of the required personnel number, the conveying port number, the speed of the identification device, the speed of the classification device and the speed of the conveying device by solving two goals of minimizing the required resources and the sorting time;
the real-time optimization control unit is used for real-time optimization control, the optimal value of the speed of the conveying device, which is given by the plan scheduling unit, is used as an initial set value, a process set value of the speed of the conveying device is given according to the speed of the identification device and the speed of the classification device, and the set value is sent to the local control unit.
2. The logistics parcel sorting system based on artificial intelligence as claimed in claim 1, wherein said failure diagnosis unit comprises a failure diagnosis analysis module and a failure diagnosis sensor, said failure diagnosis sensor is arranged on said identification means, said sorting means, said conveying means, respectively, measuring data; the fault diagnosis sensor sends the measurement data to the fault diagnosis analysis module, and the fault diagnosis analysis module analyzes the fault states of the identification device, the classification device and the conveying device according to the measurement data.
3. The logistics parcel sorting system based on artificial intelligence as claimed in claim 2, wherein the fault diagnosis unit gives the upper limit value of the speed of the recognition means, the upper limit value of the speed of the sorting means, the upper limit value of the conveying speed of the conveying means according to the analysis of the fault status of the recognition means, the sorting means, the conveying means.
4. The artificial intelligence based logistics parcel sorting system of claim 3, wherein the fault diagnosis unit sends the upper speed limit value of the identification means, the upper speed limit value of the classification means, the upper speed limit value of the conveying means to the scheduling unit in a period of 1-3 days.
5. The logistics parcel sorting system based on artificial intelligence, wherein the fault diagnosis unit sends the real-time upper speed limit value of the identification device, the real-time upper speed limit value of the classification device and the upper speed limit value of the conveying device to the real-time optimization control unit in a period of 1-3 hours.
6. The system of claim 1, wherein the constraints are that the number of people required is less than an upper limit of people, the number of delivery openings is less than an upper limit of delivery openings, the speed of the identification device is less than an upper limit of speed, the speed of the classification device is less than an upper limit of speed, and the speed of the delivery device is less than an upper limit of speed.
7. The artificial intelligence based logistics parcel sorting system of claim 1, wherein the scheduling unit sends the optimal values of the speed of the identification device, the speed of the sorting device, the speed of the conveying device to the real-time optimization control unit, and the real-time optimization control unit sends the optimal values as initial values of set values to the local control unit.
8. The system of claim 7, wherein the real-time optimization control unit gives a process set value of the speed of the transportation means according to the real-time upper speed limit value of the recognition means and the real-time upper speed limit value of the classification means sent by the failure diagnosis unit, and sends the process set value to the local control unit.
9. The artificial intelligence based logistics package sortation system as claimed in claim 1, wherein said identification means is communicatively coupled to said local control unit for transmitting package information to said local control unit; the local control unit is connected with the classification device through a digital IO and controls the classification device through package information.
10. The system of claim 1, wherein the conveyor is connected to the local control unit via digital IO to control the start and stop of the conveyor, and wherein the conveyor is connected to the local control unit via analog IO to control the speed of the conveyor.
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Application publication date: 20210108 |