CN108280529B - Steel coil rolling post-reservoir-area common-rail multi-unmanned-vehicle cooperative operation optimization method - Google Patents
Steel coil rolling post-reservoir-area common-rail multi-unmanned-vehicle cooperative operation optimization method Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a system for optimizing the common-rail multi-unmanned-vehicle cooperative operation of a steel coil rolled stock, wherein the method comprises the following steps: A. receiving a warehouse area hoisting task list, and dividing the task list into subtask lists aiming at the steel coil; the different subtask lists record one-time ex-warehouse or in-warehouse operation of each steel coil in different time periods; B. acquiring current driving data of multiple driving vehicles, and performing operation distribution on the multiple driving vehicles according to the current driving data and the subtask list to generate each lifting operation list of each driving vehicle; C. and arranging the cooperative operation of each travelling crane according to each lifting operation list of each travelling crane, and controlling the operation of each travelling crane according to the cooperative operation list. Therefore, the embodiment of the invention is beneficial to reducing the traffic avoidance.
Description
Technical Field
The invention relates to the field of unmanned crane lifting operation, in particular to a method and a system for optimizing common-rail multi-unmanned crane cooperative operation in a steel coil rolling post-storage area.
Background
In the unmanned travelling crane lifting system, when a plurality of travelling cranes work together, the travelling cranes cannot cross each other because the travelling cranes are on the same track, so that how to effectively optimize the lifting plan of the travelling cranes, reduce or even avoid travelling crane avoidance, shorten the overall travelling distance of the multi-row vehicles, reduce power energy consumption and illumination energy consumption, save the total lifting time, and the system is a key link for energy conservation and emission reduction of the common rail multi-row vehicle lifting system and is a key point for controlling the operation cost of a warehouse.
The reservoir area common rail multi-row vehicle cooperative operation optimization system distributes the operation of common rail multi-row vehicles, so that the total required avoiding route is shortest when the multi-row vehicles run simultaneously. However, in a traditional manually operated warehouse, the operation distribution of steel coil lifting is judged by workers at the warehouse, and a plurality of driving drivers are instructed to carry out lifting. Under the condition that the number of traveling cranes is large and the flow of steel coils is large, a plurality of traveling cranes often perform cross operation and need to avoid. The conventional manual random co-rail multi-row vehicle collaborative operation hoisting scheme lacks a good operation optimization method to guide the driving work, so that a corresponding operation optimization method needs to be researched and developed at present to improve the hoisting labor efficiency, stop manual illegal hoisting, reduce the accident rate, reduce or even avoid driving avoidance, shorten the integral walking distance of the multi-row vehicle, reduce the driving hoisting time and improve the driving utilization rate.
Disclosure of Invention
In view of the above, the invention provides a method and a system for optimizing the co-rail multi-unmanned travelling crane collaborative operation of a steel coil rolling post-storage, so as to improve the lifting labor efficiency, stop artificial illegal lifting, reduce the accident rate, reduce or even avoid travelling crane avoidance, shorten the overall travelling distance of multiple travelling cranes, reduce the travelling crane lifting time and improve the travelling crane utilization rate.
The invention provides a method for optimizing the common-rail unmanned crane collaborative operation of a steel coil rolled reservoir area, which comprises the following steps:
A. receiving a warehouse area hoisting task list, and dividing the task list into subtask lists aiming at the steel coil; the different subtask lists record one-time ex-warehouse or in-warehouse operation of each steel coil in different time periods;
B. acquiring current driving data of multiple driving vehicles, and performing operation distribution on the multiple driving vehicles according to the current driving data and the subtask list to generate each lifting operation list of each driving vehicle;
C. and arranging the cooperative operation of each travelling crane according to each lifting operation list of each travelling crane, and controlling the operation of each travelling crane according to the cooperative operation list.
Step A the dividing comprises:
determining the different warehouse-in and warehouse-out opening requirements of the steel coils in different time periods recorded in the warehouse area lifting task list; and generating different subtask lists corresponding to different time periods, and recording the operation of each steel coil aiming at a certain warehouse inlet and outlet only once in each subtask list in the time period.
By above, be favorable to reducing the driving and dodge, shorten the holistic travel distance of driving more, improve handling labor efficiency, reduce driving handling time, improve the driving utilization ratio.
And step B, the step of generating each lifting operation list of each traveling crane comprises the following steps:
and (3) counting the flow of each warehouse inlet and outlet in the recording time period of each subtask list, and performing operation distribution on the vehicles in multiple rows as follows:
when the flow of a certain warehouse inlet and outlet port is centralized in a certain time period, distributing the subtasks corresponding to the time period and the same or similar warehouse inlet and outlet port positions to each travelling crane simultaneously;
wherein, the dividing of step a includes:
determining the different warehouse-in and warehouse-out opening requirements of the steel coils in different time periods recorded in the warehouse area lifting task list; generating different subtask lists corresponding to different time periods, and recording the operation of each steel coil for a certain warehouse inlet and outlet only once in each subtask list in the time period;
and step B, the step of generating each lifting operation list of each traveling crane comprises the following steps:
and (3) counting the flow of each warehouse inlet and outlet in the recording time period of each subtask list, and performing operation distribution on the vehicles in multiple rows as follows:
when the flow of a certain warehouse inlet and outlet is centralized in a certain time period, the subtasks corresponding to the time period and the position of the same or similar warehouse inlet and outlet are simultaneously distributed to each traveling crane,
and (4) counting the flow conditions of the sub-task list warehouse-in and warehouse-out areas in the current time period, namely counting the quantity of the steel coils at different entrances and exits respectively.
Si＝∑Ai st.(Ai fromi,i＝1…m1)
Sj＝∑Aj st.(Aj toj,j＝1…n1)
Wherein m is1The number of the warehouse-in ports i is; n is1The number of the warehouse-out ports j is; a. theiThe steel coil is put in storage from a storage port i; a. thejThe steel coil is delivered from a delivery port j; siThe sum of steel coils put in the warehouse from the warehouse inlet i; sjThe sum of the steel coils delivered from the delivery outlet j.
Bundling strategy st. (σ2Si+σ2Sj)＞ε
Wherein, a variance threshold value epsilon and S are setiHas a variance of σ2Si，SjHas a variance of σ2SjAnd determining whether the flow is concentrated or not according to the variance of the quantity of the steel coils at different inlets and outlets.
The method comprises the following steps of implementing a binding strategy to a time period with concentrated flow to obtain a binding and hoisting operation sheet, classifying similar tasks by the binding strategy, obtaining a multi-vehicle binding operation and hoisting operation sheet aiming at different types, classifying the hoisting tasks with the same or similar exit and entrance positions into one type, assigning the same type of tasks to different vehicles to realize synchronous operation of the multi-vehicle, storing steel coils of the tasks with the same or similar exit and entrance positions at the similar positions when the strategy is selected to operate, and calculating the mutual distance of the entrance positions as follows:
wherein (x)i1,yi1,zi1) Is the coordinate of the warehouse entry i1, (x)i2,yi2,zi2) Coordinates of the entry i2, di1i2(x) is the distance between the entrance opening i1 and the entrance opening i2j1,yj1,zj1) Is the coordinate of the warehouse-out port j1, (x)j2,yj2,zj2) Is the coordinate of the warehouse-out port j2, dj1j2Is the distance between the outlet j1 and the outlet j 2.
Setting thresholds xi 1 and xi 2, considering that the entrance distance is smaller than xi 1 as a similar position, the exit distance is smaller than xi 2 as a similar position, defining the warehousing ports with similar positions as warehousing ports k, and totally m2Defining the similar warehouse-in ports as warehouse-out ports l with the similar positions, and having n in total2Similar exit and entrance positions can be classified as:
k st.di1i2＜ξ1(k＝1…m2,m2≤m1)
l st.dj1j2＜ξ2(l＝1…n2,n2≤n1)
if the steel coil A starts from a similar inlet k and goes to a similar outlet l, the subtask list can be expressed as:
wherein the similar tasks are hoisting tasks with similar entrances and exits:
Γ＝Aij st.(Aifromki,tolj)
wherein A isijIndicating the coil of steel AijStarting from the ith similar inlet ki to the jth similar outlet lj.
And aiming at the situation that the flow of the warehouse inlet and the warehouse outlet is not concentrated and the warehouse inlet and the warehouse outlet are scattered in a certain period, distributing each subtask to each traveling crane according to the flow balance principle in each preset designated operation area or each operation area formed by the average distribution warehouse area.
By above, be favorable to improving handling efficiency, reduce the driving and dodge, shorten the holistic walking distance of driving a plurality of, reduce driving handling time, improve driving utilization ratio, reduce the accident rate.
Preferably, the step C of arranging the cooperative work of the traveling cranes comprises:
each travelling crane takes a certain mutual interval position as a starting position;
starting the travelling cranes at the same time in a no-load way, and moving the travelling cranes at the same speed and direction until the travelling cranes reach the steel coil position respectively; each travelling crane finishes the action of grabbing the steel coil; starting the travelling cranes with loads at the same time, and moving the travelling cranes at the same speed and in the same direction until the travelling cranes reach the expected steel coil laying-down positions respectively; and each crane finishes the action of putting down the steel coil.
By above, be favorable to reducing the driving and dodge, shorten the holistic travel distance of driving more, improve handling labor efficiency, reduce driving handling time, improve the driving utilization ratio.
Preferably, the step C of controlling the operation of each traveling crane further includes:
D. acquiring the driving direction and position of each vehicle in real time;
when the current speed of a certain vehicle exceeds a specified threshold value or the distance between vehicles is less than a specified distance or the driving direction deviates from a specified direction, if the two vehicles move in the same direction, a rear vehicle stopping strategy is adopted; if the two vehicles move in opposite directions, priority avoidance or shortest path avoidance is adopted.
Therefore, the collision of the travelling crane is avoided, and the accident rate is reduced.
The invention also provides a system for optimizing the common-rail multi-unmanned-vehicle cooperative operation in the reservoir area after the steel coil rolling, which comprises the following components:
the system comprises a system database, an artificial intelligence control module, a multi-line vehicle operation scheduling module, a multi-line vehicle cooperative operation module, a traveling operation basic automation module and a data communication module which is connected with the modules for mutual communication;
wherein the system database is used for storing a plurality of rows of vehicle-related data;
the artificial intelligence control module is used for hoisting a task list in a warehouse area, acquiring current driving data of multiple rows of vehicles and related data of multiple driving vehicles from a system database, providing the data to the operation scheduling module of the multiple rows of vehicles to generate operation distribution of the multiple driving vehicles, and controlling the driving operation basic automation module to execute the operation of the driving vehicles according to the task of the multiple rows of vehicles in cooperation with the operation module.
By above, be favorable to improving handling efficiency, reduce the driving and dodge, shorten the holistic walking distance of driving a plurality of, reduce driving handling time, improve driving utilization ratio, reduce the accident rate.
Preferably, the system further comprises: and the artificial intelligence module is also used for carrying out driving danger avoidance on the multi-row vehicle according to the danger avoiding method provided by the multi-row vehicle danger avoiding module.
In summary, the invention provides a method and a system for optimizing multi-unmanned vehicle cooperative operation of a common rail of a steel coil rolling post-storage, which propose to schedule multi-vehicle cooperative operation optimization calculation by an artificial intelligence module from the perspective of reasonably issuing vehicle operation tasks, and consider cooperative operation implementation and risk avoidance, so that the multi-vehicle operates according to an optimized operation sequence, and the multi-vehicle operation optimization effect is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of the multi-unmanned-vehicle cooperative operation of the steel coil rolled stock common rail;
FIG. 2 is a flow chart of the optimization method for the common rail multi-unmanned traveling crane collaborative operation of the steel coil rolling post-storage warehouse;
FIG. 3 is a functional structure diagram of a common rail multi-unmanned traveling crane collaborative operation optimization system of a steel coil post-rolling warehouse of the invention;
FIG. 4 is a schematic diagram of the operational principle of the artificial intelligence control module of the present invention;
FIG. 5 is a schematic diagram of the operating principle of the multi-row vehicle job scheduling module of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. 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.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 one
The invention provides a common rail multi-unmanned travelling cooperative operation optimization system for a steel coil rolling post-storage, which is used for scheduling multi-row vehicle cooperative operation optimization calculation by an artificial intelligence module from the perspective of reasonably issuing travelling operation tasks, and takes the implementation and risk avoidance of cooperative operation into consideration, so that the multi-row vehicle operates according to an optimized operation sequence, and the optimization effect of the multi-row vehicle operation is achieved.
The common rail multi-unmanned driving cooperative work optimization method of the invention is further described with reference to the accompanying drawings and the embodiment. As shown in fig. 1, the schematic diagram of the steel coil rolling post-rolling warehouse that multiple unmanned vehicles run on a common rail, the multiple unmanned vehicles operate simultaneously, and different steel coils are lifted to different places is shown, wherein 1 in fig. 1 is a vehicle and 2 is a rail.
As shown in FIG. 2, the method for optimizing the acceptance operation of the common rail multi-row train system of the rolled steel coil stock is provided. The method comprises the following specific steps:
s201, receiving a warehouse area hoisting task list, and dividing the task list into subtask lists aiming at steel coils; and the different subtask lists record one-time ex-warehouse or in-warehouse operation of each steel coil in different time periods.
Wherein the dividing comprises: determining the different warehouse-in and warehouse-out opening requirements of the steel coils in different time periods recorded in the warehouse area lifting task list; and generating different subtask lists corresponding to different time periods, and recording the operation of each steel coil aiming at a certain warehouse inlet and outlet only once in each subtask list in the time period.
For example, receiving a warehouse handling job ticket. Defining the hoisting variable of a single steel coil to be omegai＝(Ai,fromi,toi). Wherein A isiFor coils of steel waiting for handling in this batch, fromi,toiRespectively, the source and destination of the steel coil. Assuming the libraryIf there are m warehouse-in ports and n warehouse-out ports, the hoisting task list can be expressed as omega ═ a (a)1…Aa,from1…fromm,to1…ton). Further, according to different requirements of ex-warehouse and in-warehouse of each steel coil, the task list aiming at the warehouse is divided into subtask lists aiming at the steel coils. The subtask list only operates one steel coil once according to different periods, namely a proper period is selected, so that each steel coil only enters or leaves the warehouse in the period. If the steel coil is required to be stored and discharged in the period, the steel coil is directly lifted from the storage port to the discharge port. Suppose that the subtask list includes b coils from m1Entering a warehouse through a warehouse entrance, n1If the individual warehouse-out port goes out of the warehouse, the subtask list can be expressed as
Wherein,
and S202, distributing the operation of the multiple rows of vehicles according to the subtask list to generate each lifting operation list of each vehicle.
Wherein, the step of generating each handling operation list of each driving includes:
and (3) counting the flow of each warehouse inlet and outlet in the recording time period of each subtask list, and performing operation distribution on the vehicles in multiple rows as follows: when the flow of a certain warehouse inlet and outlet port is centralized in a certain time period, distributing the subtasks corresponding to the time period and the same or similar warehouse inlet and outlet port positions to each travelling crane simultaneously; and aiming at the situation that the flow of the warehouse inlet and the warehouse outlet is not concentrated and the warehouse inlet and the warehouse outlet are scattered in a certain period, distributing each subtask to each traveling crane according to the flow balance principle in each preset designated operation area or each operation area formed by the average distribution warehouse area.
Specifically, for example, in the first step, the conditions of the warehouse-in and warehouse-out flow of the subtask list warehouse area in the current time period are counted. Namely, the quantity of the steel coils at different inlets and outlets is respectively counted.
Si＝∑Ai st.(Ai fromi,i＝1…m1)
Sj＝∑Aj st.(Aj toj,j＝1…n1)
Wherein m is1The number of the warehouse-in ports i is; n is1The number of the warehouse-out ports j is; a. theiThe steel coil is put in storage from a storage port i; a. thejThe steel coil is delivered from a delivery port j; siThe sum of steel coils put in the warehouse from the warehouse inlet i; sjThe sum of the steel coils delivered from the delivery outlet j.
Secondly, selecting different scheduling strategies according to different conditions of the flow of the warehouse in and out, and selecting a binding strategy if the flow of the warehouse in and out is concentrated from the same port in the period; and if the access is balanced and the access is scattered, selecting a partitioning strategy. Wherein, a variance threshold value epsilon and S are setiHas a variance of σ2Si，SjHas a variance of σ2SjAnd determining whether the flow is concentrated or not according to the variance of the quantity of the steel coils at different inlets and outlets.
Bundling strategy st. (sigma)2Si+σ2Sj)＞ε
Partition strategy st. (σ)2Si+σ2Sj)＜ε
And thirdly, implementing a binding strategy in a time period with concentrated flow to obtain a binding and hoisting operation list, and implementing a partitioning strategy in a time period without concentration to obtain a partitioning and hoisting operation list.
If the binding strategy is selected, the similar tasks are classified firstly, and the multi-vehicle binding operation handling operation list is obtained according to different types. Lifting tasks with the same or similar access opening positions are considered to be classified into a category. And the same kind of tasks are assigned to different traveling cranes, so that synchronous work of multiple traveling cranes is realized. When the strategy is selected to work, the steel coils with the same or similar tasks at the inlet and the outlet are stored at the similar positions. The mutual distance of the entry positions is calculated as follows:
wherein (x)i1,yi1,zi1) Is the coordinate of the warehouse entry i1, (x)i2,yi2,zi2) Coordinates of the entry i2, di1i2Is the distance between the inlet i1 and the inlet i 2. (x)j1,yj1,zj1) Is the coordinate of the warehouse-out port j1, (x)j2,yj2,zj2) Is the coordinate of the warehouse-out port j2, dj1j2Is the distance between the outlet j1 and the outlet j 2.
Setting thresholds xi 1 and xi 2, considering that the entrance distance is smaller than xi 1 as a similar position, the exit distance is smaller than xi 2 as a similar position, defining the warehousing ports with similar positions as warehousing ports k, and totally m2Defining the similar warehouse-in ports as warehouse-out ports l with the similar positions, and having n in total2Similar warehouse outlet. The entrance and exit positions can be classified as:
k st.di1i2＜ξ1(k＝1…m2,m2≤m1)
l st.dj1j2＜ξ2(l＝1…n2,n2≤n1)
if the steel coil A starts from a similar inlet k and goes to a similar outlet l, the subtask list can be expressed as:
wherein the similar tasks are hoisting tasks with similar entrances and exits:
Γ＝Aij st.(Aifromki,tolj)
wherein A isijIndicating the coil of steel AijStarting from the ith similar inlet ki to the jth similar outlet lj.
And if the binding operation of the similar tasks is executed, the similar tasks are simultaneously issued to the multiple traveling vehicles for execution. If the operation is warehousing, the multiple rows of vehicles respectively drive to the position of a similar steel coil warehousing opening, the multiple rows of vehicles simultaneously grab the steel coils, the multiple rows of vehicles simultaneously drive to the position of the similar steel coil warehousing area, and the multiple rows of vehicles simultaneously put down the steel coils. If the operation of ex-warehouse is carried out at the moment, the multi-row vehicles respectively drive to the positions of the similar steel coil warehouse areas, the multi-row vehicles simultaneously grab the steel coils, the multi-row vehicles simultaneously drive to the positions of the similar steel coil ex-warehouse openings, and the multi-row vehicles simultaneously put down the steel coils.
For dissimilar tasks, the bicycle is operated, and the other bicycles are kept away. Or to perform a multi-vehicle zone strategy.
And if the partition strategy is selected, partitioning different tasks to obtain a partition lifting operation list. The partitioning principle can be performed according to the process requirements, such as a process designating a certain area of a certain traveling crane operation. Because the partitions are selected under the condition of flow balance, the pool areas can be evenly distributed or the outlets and inlets can be evenly distributed if no special requirement exists. If the reservoir is divided into a region a, a region b and a region c, the region a comprises an inlet 1 and an outlet 1 and is positioned at the south of the reservoir, the region b comprises an inlet 2 and an outlet 2 and is positioned at the middle of the reservoir, the region c comprises an inlet 3 and an outlet 3 and is positioned at the north of the reservoir, and the travelling crane A, B, C respectively operates the region a, the region b and the region c without cross-region operation. If the cross-region operation is needed, a certain driving vehicle is appointed to operate, and other vehicles are protected from danger.
And S203, arranging the cooperative operation of the traveling cranes according to the lifting operation lists of the traveling cranes, and controlling the operation of the traveling cranes according to the cooperative operation lists.
Wherein the scheduling of the cooperative work of the respective traveling vehicles includes:
each travelling crane takes a certain mutual interval position as a starting position;
starting the travelling cranes at the same time in a no-load way, and moving the travelling cranes at the same speed and direction until the travelling cranes reach the steel coil position respectively; each travelling crane finishes the action of grabbing the steel coil; starting the travelling cranes with loads at the same time, and moving the travelling cranes at the same speed and in the same direction until the travelling cranes reach the expected steel coil laying-down positions respectively; and each crane finishes the action of putting down the steel coil.
Wherein, the operation of controlling each driving still includes: acquiring the driving direction and position of each vehicle in real time; when the current speed of a certain vehicle exceeds a specified threshold value or the distance between vehicles is less than a specified distance or the driving direction deviates from a specified direction, if the two vehicles move in the same direction, a rear vehicle stopping strategy is adopted; if the two vehicles move in opposite directions, priority avoidance or shortest path avoidance is adopted.
Example two
Based on the method for optimizing the co-rail multi-unmanned-vehicle cooperative operation of the steel coil rolled stock, the application also provides a system for optimizing the co-rail unmanned-vehicle cooperative operation of the steel coil rolled stock, which comprises the following steps:
the system comprises a system database, an artificial intelligence control module, a multi-line vehicle operation scheduling module, a multi-line vehicle cooperative operation module, a traveling operation basic automation module and a data communication module which is connected with the modules for mutual communication;
wherein the system database is used for storing a plurality of rows of vehicle-related data; the artificial intelligence control module is used for hoisting a task list in a warehouse area, acquiring current driving data of multiple rows of vehicles and related data of multiple driving vehicles from a system database, providing the data to the operation scheduling module of the multiple rows of vehicles to generate operation distribution of the multiple driving vehicles, and controlling the driving operation basic automation module to execute the operation of the driving vehicles according to the task of the multiple rows of vehicles in cooperation with the operation module.
Preferably, the system further comprises: and the artificial intelligence module is also used for carrying out driving danger avoidance on the multi-row vehicle according to the danger avoiding method provided by the multi-row vehicle danger avoiding module.
Specifically, the system database is used for storing a plurality of rows of vehicle operation related data. The relevant data includes: the system comprises data such as multi-row vehicle operation data, multi-row vehicle operation optimization results, multi-row vehicle hoisting task list historical records, steel coil hoisting task list historical records, multi-row vehicle hoisting process historical records, multi-row vehicle risk avoidance historical records, multi-row vehicle abnormity historical records and the like. Multiple rows of vehicle operating data include, but are not limited to: according to the type, format, detection precision and sampling period of the multi-vehicle data required by the operation optimization method; the current running speed, acceleration and position of the multi-vehicle; the current working states of stopping, grabbing, lifting, putting down and the like of the multi-row vehicle; the name and the classification model of the specific steel coil currently grabbed by the multi-traveling crane. The work optimization results of the multiple traveling vehicles include but are not limited to: the operation of the multiple traveling cranes is matched in sequence, namely when the A traveling crane hoists the steel coil A, the B traveling crane hoists the steel coils B1 and B2, and the like. The hoisting optimization sequence of the multiple travelling cranes is the sequencing sequence of the goods hoisted by each travelling crane; the specific advancing route of the multiple traveling vehicles is the specific advancing route of the goods hoisted by the multiple traveling vehicles in the xyz axis direction; the operation optimization progress degree of the current tasks of the multi-row vehicles is that the multi-row vehicles are lifting the number one in the batch. The multi-car handling job ticket history record includes but is not limited to: and (4) listing all the task lists lifted by the historical multi-row vehicles. The history record of the handling task list of the steel coil includes but is not limited to: the method comprises a steel coil warehousing list, a steel coil ex-warehouse list and flow lists of all entrances and exits of a warehouse. The history of the multi-car handling process includes but is not limited to: and a plurality of rows of action records of the vehicle history at each moment. The multi-row vehicle abnormity history record comprises, but is not limited to, the time when the abnormity occurs in the multi-row vehicle, the abnormity type and the abnormity processing scheme. Namely, the system database is used for storing data of the artificial intelligence control module, the multi-row vehicle operation scheduling module, the multi-row vehicle cooperative operation module, the multi-row vehicle risk avoiding module and the data communication module.
The data communication module is used for data communication. The module collects data from a PLC (programmable logic controller) and/or DCS (distributed control system) system on site, adopts a TCP/IP (transmission control protocol/Internet protocol) communication protocol to communicate the collected driving operation data with a PC (personal computer), reads and stores required data in real time through a corresponding database access technology, and enters a system database. The PLC and the DCS are arranged in the traveling crane operation system.
The artificial intelligence control module is responsible for calling and controlling modules. As shown in fig. 4, the specific implementation steps are as follows: s401, receiving a traveling crane lifting task list. Defining the hoisting variable of a single steel coil to be omegai＝(Ai,fromi,toi). Wherein A isiFor coils of steel waiting for handling in this batch, fromi,toiRespectively, the source and destination of the steel coil. Assuming that the warehouse has m warehouse inlets and n warehouse outlets, the hoisting task list can be expressed as omega (a)1…Aa,from1…fromm,to1…ton). S402, according to the difference of each steel coilAnd dividing the task list aiming at the warehouse into subtasks aiming at the steel coils according to the requirements of warehouse-in and warehouse-out. The subtask list only operates one steel coil once according to different periods, namely a proper period is selected, so that each steel coil only enters or leaves the warehouse in the period. If the steel coil is required to be stored and discharged in the period, the steel coil is directly lifted from the storage port to the discharge port. Suppose that the subtask list includes b coils from m1Entering a warehouse through a warehouse entrance, n1If the individual warehouse-out port goes out of the warehouse, the subtask list can be expressed as
Wherein,
and S403, calling a multi-vehicle operation scheduling module, and obtaining each lifting operation sheet of the multi-vehicle according to the subtask sheet. Specifically, a binding strategy is implemented for a time period with concentrated flow, a binding and hoisting operation sheet is obtained, a partitioning strategy is implemented for a time period without concentration, and a partitioning and hoisting operation sheet is obtained. And selecting the travelling crane corresponding to the subarea to execute the corresponding hoisting operation list according to the subarea strategy. Namely obtaining the hoisting operation sheet of the traveling crane k
Lifting operation sheet of travelling crane
If more traveling vehicles exist, the rest can be done in the same way. And S404, calling the multi-vehicle cooperative operation module, arranging the multi-vehicle cooperative work, and issuing the multi-vehicle cooperative task to the basic automation. S405, communicating with the data communication module, judging the current state of the multi-row vehicle, and estimating the positions of the multi-row vehicle after the current task batch is finished. S406, calling a traveling crane operation basic automation module to control an execution line according to each lifting operation list of multiple traveling cranes, multiple-row vehicle cooperative operation tasks and the estimated positions of multiple traveling cranes after the current task batch is finishedAnd (5) running the vehicle. S407, for example, arranging multiple driving refuges in the job order, or refuges are needed when meeting emergency in the process of executing multiple lines of vehicles. And calling the multi-vehicle risk avoiding module to guide the multi-vehicle to avoid risks. And S408, if the abnormal phenomenon of multiple vehicles occurs, the artificial intelligence control module sends an interrupt to carry out intelligent processing or wait for artificial processing on multiple vehicles. And S409, after the problem is processed, continuously issuing or re-issuing the multi-row vehicle hoisting operation instruction.
The multi-vehicle operation scheduling module is responsible for scheduling multi-vehicle operation, namely sending a reasonable arrangement order to the multi-vehicle, so that the condition of mutual avoidance is reduced or even avoided when the multi-vehicle operates simultaneously. As shown in fig. 5, the specific implementation steps are as follows:
s501, counting the flow rate of the sub-task list warehouse-in and warehouse-out in the current time period. Namely, the quantity of the steel coils at different inlets and outlets is respectively counted.
Si＝∑Ai st.(Ai fromi,i＝1…m1)
Sj＝∑Aj st.(Aj toj,j＝1…n1)
Wherein m is1The number of the warehouse-in ports i is; n is1The number of the warehouse-out ports j is; a. theiThe steel coil is put in storage from a storage port i; a. thejThe steel coil is delivered from a delivery port j; siThe sum of steel coils put in the warehouse from the warehouse inlet i; sjThe sum of the steel coils delivered from the delivery outlet j.
S502, according to different conditions of the flow entering and exiting the warehouse, different scheduling strategies are selected, and if the flow enters and exits the warehouse from the same outlet in the period or the flow entering the warehouse is concentrated, a binding strategy is selected; and if the access is balanced and the access is scattered, selecting a partitioning strategy. Wherein, a variance threshold value epsilon and S are setiHas a variance of σ2Si，SjHas a variance of σ2SjAnd determining whether the flow is concentrated or not according to the variance of the quantity of the steel coils at different inlets and outlets.
Bundling strategy st. (sigma)2Si+σ2Sj)＞ε
Partition strategy st. (σ)2Si+σ2Sj)＜ε
Wherein, a binding strategy is implemented for a time period with concentrated flow, and a partitioning strategy is implemented for a time period without concentration;
wherein if the bundling policy is enforced, S503 is performed; if the partition policy is enforced, S505 is performed.
S503, if the binding strategy is selected, firstly classifying the similar tasks, and issuing a multi-vehicle binding operation handling operation sheet according to different types. Lifting tasks with the same or similar access opening positions are considered to be classified into a category. And the same kind of tasks are assigned to different traveling cranes, so that synchronous work of multiple traveling cranes is realized. When the strategy is selected to work, the steel coils with the same or similar tasks at the inlet and the outlet are stored at the similar positions. The mutual distance of the entry positions is calculated as follows:
wherein (x)i1,yi1,zi1) Is the coordinate of the warehouse entry i1, (x)i2,yi2,zi2) Coordinates of the entry i2, di1i2Is the distance between the inlet i1 and the inlet i 2. (x)j1,yj1,zj1) Is the coordinate of the warehouse-out port j1, (x)j2,yj2,zj2) Is the coordinate of the warehouse-out port j2, dj1j2Is the distance between the outlet j1 and the outlet j 2.
Setting thresholds xi 1 and xi 2, considering that the entrance distance is smaller than xi 1 as a similar position, the exit distance is smaller than xi 2 as a similar position, defining the warehousing ports with similar positions as warehousing ports k, and totally m2Defining the similar warehouse-in ports as warehouse-out ports l with the similar positions, and having n in total2Similar warehouse outlet. The entrance and exit positions can be classified as:
k st.di1i2＜ξ1(k＝1…m2,m2≤m1)
l st.dj1j2＜ξ2(l＝1…n2,n2≤n1)
if the steel coil A starts from a similar inlet k and goes to a similar outlet l, the subtask list can be expressed as:
wherein the similar tasks are hoisting tasks with similar entrances and exits:
Γ＝Ai st.(Aifromki,toli)
wherein A isijIndicating the coil of steel AijStarting from the ith similar inlet ki to the jth similar outlet lj.
And S504, executing the binding operation of the similar tasks, and simultaneously issuing the similar tasks to the multiple traveling vehicles for execution. If the operation is warehousing, the multiple rows of vehicles respectively drive to the position of a similar steel coil warehousing opening, the multiple rows of vehicles simultaneously grab the steel coils, the multiple rows of vehicles simultaneously drive to the position of the similar steel coil warehousing area, and the multiple rows of vehicles simultaneously put down the steel coils. If the operation of ex-warehouse is carried out at the moment, the multi-row vehicles respectively drive to the positions of the similar steel coil warehouse areas, the multi-row vehicles simultaneously grab the steel coils, the multi-row vehicles simultaneously drive to the positions of the similar steel coil ex-warehouse openings, and the multi-row vehicles simultaneously put down the steel coils. The multiple traveling cranes operate simultaneously and are ensured by the multi-row vehicle cooperative operation module.
And for dissimilar tasks, performing single-vehicle operation, and calling the risk avoiding module by other vehicles to avoid risks. Or to perform a multi-vehicle zone strategy.
And S505 to S506, if the partition strategy is selected, partitioning different tasks, and issuing a multi-vehicle partition operation task list. The partitioning principle can be performed according to the process requirements, such as a process designating a certain area of a certain traveling crane operation. Because the partitions are selected under the condition of flow balance, the pool areas can be evenly distributed or the outlets and inlets can be evenly distributed if no special requirement exists. If the reservoir is divided into a region a, a region b and a region c, the region a comprises an inlet 1 and an outlet 1 and is positioned at the south of the reservoir, the region b comprises an inlet 2 and an outlet 2 and is positioned at the middle of the reservoir, the region c comprises an inlet 3 and an outlet 3 and is positioned at the north of the reservoir, and the travelling crane A, B, C respectively operates the region a, the region b and the region c without cross-region operation. If the cross-region operation is needed, a certain driving vehicle is appointed to operate, and other vehicles call the danger avoiding module to avoid danger.
And the multi-row vehicle cooperative operation module guides the multi-row vehicles to perform cooperative work according to the lifting operation list of each vehicle. The specific implementation steps are as follows: in the first step, the initial positions of a plurality of rows of vehicles are in place, the safety distance between the vehicles in the rows is guaranteed in the step, and the positions with certain mutual intervals are used as the starting positions. And secondly, starting the multiple rows of vehicles in a no-load mode at the same time, and moving the vehicles in the same speed and direction until the vehicles respectively reach the steel coil position. And thirdly, grabbing the steel coils by the multiple traveling cranes, and waiting by other traveling cranes if some traveling cranes do not complete grabbing tasks. And fourthly, simultaneously starting the vehicles with loads in multiple rows, and moving the vehicles according to the same speed and direction until the vehicles respectively reach the expected steel coil putting-down positions. And fifthly, putting down the steel coils by the multiple rows of the traveling cranes, and waiting by other traveling cranes if some traveling cranes do not finish putting down actions. The next round, from the second step cycle.
The multi-vehicle risk avoiding module guides the multi-vehicle to avoid risks according to certain rules. The specific implementation steps are as follows: in the first step, multiple vehicles communicate the position, speed, and direction of travel of other vehicles in real time. And step two, if the speed of the other traveling vehicles in the position direction reaches a certain value, considering that danger avoidance is needed. And thirdly, avoiding risks. If the two lines of vehicles move in the same direction, a rear vehicle stopping strategy is adopted; if the two lines of vehicles move in opposite directions, priority avoidance, alternate avoidance or shortest path avoidance can be adopted. And fourthly, when the position direction speed of other traveling vehicles reaches a certain value, the dangerous case is considered to be ended, and the avoided traveling vehicle is restarted.
And the driving operation basic automation module is responsible for executing the driving tasks issued by the artificial intelligence control module. Specifically, the artificial intelligence control module sends the driving operation tasks guided by the multi-row vehicle operation scheduling module, the multi-row vehicle cooperative operation module and the multi-row vehicle danger avoiding module to the driving operation basic automation module, and the artificial intelligence control module is specifically responsible for controlling the operation of the driving.
To further illustrate the technical solution of the present system, the working principle of the present system is now described as follows:
the artificial intelligence control module receives a warehouse area lifting task list and divides the task list into subtask lists aiming at the steel coil; the different subtask lists record one-time ex-warehouse or in-warehouse operation of each steel coil in different time periods; the multi-row vehicle operation scheduling module is called to obtain each lifting operation list of the multi-row vehicle through the current driving data of the multi-row vehicle and the driving related data in the database acquired by the data communication module, and the multi-row vehicle is subjected to operation distribution; and calling the multi-line vehicle cooperative operation module to guide the multi-line vehicle to perform cooperative work according to the lifting operation list. For example, multiple vehicles are arranged in a work list to avoid risks, or risks need to be avoided when emergency situations occur in the process of executing multiple vehicles. And calling the multi-vehicle risk avoiding module to guide the multi-vehicle to avoid risks. If the abnormal phenomenon happens to multiple traveling vehicles, the artificial intelligence control module sends an interrupt to intelligently process the multiple traveling vehicles or wait for the abnormal problem of artificial processing. And after the problem is processed, continuously issuing or re-issuing the multi-line vehicle hoisting operation instruction.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (3)
1. A method for optimizing the common-rail unmanned crane collaborative operation of a steel coil rolled reservoir area is characterized by comprising the following steps:
A. receiving a warehouse area hoisting task list, and dividing the task list into subtask lists aiming at the steel coil; the different subtask lists record one-time ex-warehouse or in-warehouse operation of each steel coil in different time periods;
B. according to the subtask list, carrying out operation distribution on the multiple rows of vehicles to generate each lifting operation list of each travelling vehicle;
C. arranging the cooperative operation of each travelling crane according to each lifting operation list of each travelling crane, and controlling the operation of each travelling crane according to the cooperative operation list,
wherein, the dividing of step a includes:
determining the different warehouse-in and warehouse-out opening requirements of the steel coils in different time periods recorded in the warehouse area lifting task list; generating different subtask lists corresponding to different time periods, and recording the operation of each steel coil for a certain warehouse inlet and outlet only once in each subtask list in the time period;
and step B, the step of generating each lifting operation list of each traveling crane comprises the following steps:
and (3) counting the flow of each warehouse inlet and outlet in the recording time period of each subtask list, and performing operation distribution on the vehicles in multiple rows as follows:
when the flow of a certain warehouse inlet and outlet port in a certain time period is concentrated, the subtasks corresponding to the time period and the same or similar warehouse inlet and outlet port positions are simultaneously distributed to all traveling cranes, and the method specifically comprises the following steps:
counting the flow rate of the sub-task list warehouse-in and warehouse-out in the current time period, namely counting the quantity of the steel coils at different warehouse-in and warehouse-out openings respectively,
Si＝∑Ai st.(Ai fromi,i＝1…m1)
Sj＝∑Aj st.(Aj toj,j＝1…n1)
wherein m is1The number of the warehouse-in ports i is; n is1The number of the warehouse-out ports j is; a. theiThe steel coil is put in storage from a storage port i; a. thejThe steel coil is delivered from a delivery port j; siThe sum of steel coils put in the warehouse from the warehouse inlet i; sjThe sum of the steel coils delivered from the delivery outlet j,
(σ) by st2Si+σ2Sj) Judging whether the flow is concentrated or not when the flow is more than epsilon, wherein epsilon is a set variance threshold value SiHas a variance of σ2Si，SjHas a variance of σ2Sj，
The binding strategy is implemented for the time period with concentrated flow, the binding strategy firstly classifies similar tasks, obtains the binding operation and hoisting operation lists of the multi-vehicle for different types, considers the hoisting tasks with the same or similar positions at the warehouse inlet and outlet into one type, assigns the similar tasks to different vehicles to realize the synchronous work of the multi-vehicle, stores steel coils of the tasks with the same or similar positions at the warehouse inlet and outlet at the similar positions when the strategy is selected to work,
wherein, the mutual distance of the positions of the warehousing ports is calculated as follows:
wherein (x)i1,yi1,zi1) Is the coordinate of the warehouse entry i1, (x)i2,yi2,zi2) Coordinates of the entry i2, di1i2(x) is the distance between the entrance opening i1 and the entrance opening i2j1,yj1,zj1) Is the coordinate of the warehouse-out port j1, (x)j2,yj2,zj2) Is the coordinate of the warehouse-out port j2, dj1j2The distance between the outlet j1 and the outlet j2,
setting thresholds xi 1 and xi 2, considering that the distance between the warehousing entrance and the warehousing entrance is smaller than xi 1 as a similar position, considering that the distance between the ex-warehousing entrance is smaller than xi 2 as a similar position, defining the warehousing entrance with similar positions as a warehousing entrance k, and totally m2Defining the similar warehouse-in ports as warehouse-out ports l with the similar positions, and having n in total2And similar warehouse-in and warehouse-out ports are classified into the following positions:
k st.di1i2＜ξ1(k＝1…m2,m2≤m1)
l st.dj1j2＜ξ2(l＝1…n2,n2≤n1)
if the steel coil A starts from the similar warehousing port k and goes to the similar ex-warehousing port l, the subtask list is expressed as follows:
wherein the similar tasks are similar lifting tasks at the warehouse entry and exit:
Γ＝Aij st.(Aifromki,tolj)
wherein A isijIndicating the coil of steel AijStarting from the ith similar warehousing port ki to the jth similar ex-warehousing port lj;
and aiming at the situation that the flow of the warehouse inlet and the warehouse outlet is not concentrated and the warehouse inlet and the warehouse outlet are scattered in a certain period, distributing each subtask to each traveling crane according to the flow balance principle in each preset designated operation area or each operation area formed by the average distribution warehouse area.
2. The method of claim 1, wherein the step C of scheduling the cooperative work of the traveling vehicles comprises:
each travelling crane takes a certain mutual interval position as a starting position;
starting the travelling cranes at the same time in a no-load way, and moving the travelling cranes at the same speed and direction until the travelling cranes reach the steel coil position respectively; each travelling crane finishes the action of grabbing the steel coil; starting the travelling cranes with loads at the same time, and moving the travelling cranes at the same speed and in the same direction until the travelling cranes reach the expected steel coil laying-down positions respectively; and each crane finishes the action of putting down the steel coil.
3. The method of claim 1 or 2, wherein said step C of controlling the operation of each train further comprises:
D. acquiring the driving direction and position of each vehicle in real time;
when the current speed of a certain vehicle exceeds a specified threshold value or the distance between vehicles is less than a specified distance or the driving direction deviates from a specified direction, if the two vehicles move in the same direction, a rear vehicle stopping strategy is adopted; if the two vehicles move in opposite directions, priority avoidance or shortest path avoidance is adopted.
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| CN110817220A (en) * | 2019-11-11 | 2020-02-21 | 四川长虹智能制造技术有限公司 | RGV avoiding method, RGV and RGV avoiding system |
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| CN113393022B (en) * | 2021-05-31 | 2022-05-31 | 武汉港迪智能技术有限公司 | Multi-vehicle collaborative operation method for material storage area |
| CN115557133A (en) * | 2022-07-07 | 2023-01-03 | 远峰高端装备(苏州)有限公司 | Two-end type same-rail double-vehicle safe operation scheduling control system |
| CN116493518B (en) * | 2023-02-07 | 2024-09-03 | 中交第二航务工程局有限公司 | Cloud platform-based bending and forming steel bar automatic production control system and method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102393710A (en) * | 2011-10-28 | 2012-03-28 | 无锡市星亿涂装环保设备有限公司 | Multitask production simulation schedule control system for production line travelling crane and method thereof |
| CN103194786A (en) * | 2013-04-03 | 2013-07-10 | 无锡市星亿涂装环保设备有限公司 | Scheduling control method for traveling crane for electroplating on production line |
| CN103955171A (en) * | 2014-03-19 | 2014-07-30 | 东莞市维迅机械科技有限公司 | Surface processing equipment bridge crane intelligent control method and system based on fuzzy technology |
| CN104077638A (en) * | 2013-03-27 | 2014-10-01 | 中国船舶工业综合技术经济研究院 | Portal jib crane dispatching method |
| CN105527947A (en) * | 2015-12-08 | 2016-04-27 | 安徽马钢自动化信息技术有限公司 | Slab-yard tracking and management system |
| CN106011992A (en) * | 2016-07-19 | 2016-10-12 | 雷慧敏 | Gantry electroplating system and crane control method |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6647316B2 (en) * | 2001-02-22 | 2003-11-11 | Pri Automation, Inc. | Traffic management system and method for materials handling using traffic balancing and traffic density |
| US6741921B2 (en) * | 2001-10-05 | 2004-05-25 | Caterpillar Inc | Multi-stage truck assignment system and method |
| CN103325264A (en) * | 2013-06-28 | 2013-09-25 | 上海宽岱电讯科技发展有限公司 | Intelligent transportation system of PLC and control method thereof |
-
2017
- 2017-01-06 CN CN201710010934.7A patent/CN108280529B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102393710A (en) * | 2011-10-28 | 2012-03-28 | 无锡市星亿涂装环保设备有限公司 | Multitask production simulation schedule control system for production line travelling crane and method thereof |
| CN104077638A (en) * | 2013-03-27 | 2014-10-01 | 中国船舶工业综合技术经济研究院 | Portal jib crane dispatching method |
| CN103194786A (en) * | 2013-04-03 | 2013-07-10 | 无锡市星亿涂装环保设备有限公司 | Scheduling control method for traveling crane for electroplating on production line |
| CN103955171A (en) * | 2014-03-19 | 2014-07-30 | 东莞市维迅机械科技有限公司 | Surface processing equipment bridge crane intelligent control method and system based on fuzzy technology |
| CN105527947A (en) * | 2015-12-08 | 2016-04-27 | 安徽马钢自动化信息技术有限公司 | Slab-yard tracking and management system |
| CN106011992A (en) * | 2016-07-19 | 2016-10-12 | 雷慧敏 | Gantry electroplating system and crane control method |
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|---|---|
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