CN115145796B - Wharf operating system efficiency evaluation method and wharf digital simulation platform - Google Patents
Wharf operating system efficiency evaluation method and wharf digital simulation platform Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3457—Performance evaluation by simulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3447—Performance evaluation by modeling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3452—Performance evaluation by statistical analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3495—Performance evaluation by tracing or monitoring for systems
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses an evaluation method of wharf operating system efficiency and a wharf digital simulation platform, wherein the method is applied to the wharf digital simulation platform and comprises the following steps: determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system TOS, and controlling the target simulation equipment to execute the target task at a specified multiple speed according to the task execution logic; displaying an execution process of a target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding simulation data in the execution process back to the TOS in real time; when the target task is executed, determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process; the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a process technology and a business rule model of a physical reality wharf under the TOS, so that efficiency, accuracy and safety of a wharf operating system during performance evaluation are improved.
Description
Technical Field
The application relates to the technical field of container terminals, in particular to a method for evaluating the efficiency of a terminal operating system and a terminal digital simulation platform.
Background
The TOS (Terminal Operation System, wharf operating System) is the brain of the wharf, and especially for a comprehensive large-scale container wharf, the powerful support of the TOS cannot be left behind due to efficient Operation efficiency, intelligent Operation means and green and environment-friendly operating environment. To ensure that the performance of TOS can be matched with the container terminal business in rapid domestic development, it is necessary to continuously perform production efficiency and energy consumption evaluation tests on TOS.
At present, aiming at the test and evaluation of the production efficiency of TOS, verification is mainly carried out by putting into actual production, and data statistics and efficiency analysis in the process of putting into production test are completed manually.
The following problems exist only by performing a realistic commissioning test on TOS:
1. the test period is long, and the time cost is high;
2. the system is frequently switched, the production is interfered, and the production stopping cost is high;
3. the data in the production process is difficult to count, and the analysis result is not accurate;
4. the algorithm may have a vulnerability and the test has a security risk.
Therefore, how to improve efficiency, accuracy and safety when performing performance evaluation on the code head operating system is a technical problem to be solved at present.
Disclosure of Invention
The invention provides an evaluation method of wharf operating system efficiency, which is used for solving the technical problems of low efficiency, poor accuracy and low safety when the wharf operating system is evaluated in the prior art, and the method is applied to a wharf digital simulation platform and comprises the following steps:
determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system (TOS), and controlling the target simulation equipment to execute the target task at a specified speed according to the task execution logic;
displaying the execution process of the target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding back simulation data in the execution process to the TOS in real time so that the TOS can update an instruction database in real time;
when the target task is executed, determining an evaluation result of the efficiency of the TOS according to data of a preset evaluation index in the execution process;
the terminal digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a flow process and a business rule model of a physical reality terminal under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user.
In some embodiments of the present application, before determining the target simulation device, the target task, and the task execution logic according to a scheduling instruction issued by a wharf operating system TOS, the method further includes:
receiving the scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
In some embodiments of the application, the real-time feedback of the simulation data in the execution process to the TOS specifically includes:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the execution data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, a device state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
In some embodiments of the present application, before determining the evaluation result of the TOS performance according to the data of the preset evaluation index in the execution process, the method further includes:
constructing a correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation focus point;
determining the preset evaluation index based on the correlation mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scores.
In some embodiments of the present application, the TOS establishes the connection with the digital simulation platform of the wharf based on connecting a first IP address and disconnecting a second IP address, and the TOS establishes the connection with the physical reality wharf based on connecting the second IP address and disconnecting the first IP address.
Correspondingly, the invention also provides a wharf digital simulation platform, which comprises:
the simulation management module is used for determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system (TOS), and controlling the target simulation equipment to execute the target task at a specified multiple speed according to the task execution logic;
the display module is used for displaying the execution process of the target task in real time based on a preset three-dimensional graphic rendering algorithm;
the feedback module is used for feeding back simulation data in the execution process to the TOS in real time so that the TOS can update the instruction database in real time;
the efficiency evaluation module is used for determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process when the target task is completely executed;
the terminal digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a flow process and a business rule model of a physical reality terminal under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user.
In some embodiments of the present application, the platform further comprises:
the Redis analysis module is used for receiving the scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
In some embodiments of the present application, the feedback module is specifically configured to:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the execution data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, a device state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
In some embodiments of the present application, the platform further includes a data management and storage module, integrated with the simulation management module, for:
constructing a correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation focus point;
determining the preset evaluation index based on the association mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scoring.
In some embodiments of the present application, the platform further comprises:
the port management module is used for carrying out shore line management, storage yard management, card collection management and message management;
the human-computer interaction module is used for carrying out UI management, scene browsing management and simulation scenario editing;
the algorithm module is used for calculating lane selection and manual instruction selection;
the exception management module is used for storing exception logs and giving an exception prompt and an alarm;
the digital wharf base comprises a three-dimensional rendering module and a GIS module and is used for providing an algorithm for graphic rendering and coordinate unification;
the human-computer interaction module, the algorithm module, the abnormity management module, the simulation management module, the feedback module and the efficiency evaluation module are respectively connected with the port management module, the display module is integrated with the human-computer interaction module, and the digital wharf base is the bottom layer of the wharf digital simulation platform.
By applying the technical scheme, the target simulation equipment, the target task and the task execution logic are determined according to a scheduling instruction issued by a wharf operating system TOS, and the target simulation equipment is controlled to execute the target task at the specified double speed according to the task execution logic; displaying an execution process of a target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding simulation data in the execution process back to the TOS in real time so that the TOS can update an instruction database in real time; when the target task is executed, determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process; the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a process technology and a business rule model of a physical reality wharf under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user, so that efficiency, accuracy and safety of performance evaluation of the wharf operating system are improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart illustrating an evaluation method for the performance of a dock operating system according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a principle of a method for evaluating the performance of a wharf operating system according to an embodiment of the present invention;
fig. 3 shows a schematic structural diagram of a digital simulation platform for a wharf according to an embodiment of the present invention;
fig. 4 shows a schematic structural diagram of a digital simulation platform for a wharf according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
The embodiment of the application provides an evaluation method of wharf operating system efficiency, which is characterized in that a wharf digital simulation platform is built through simulating container wharf equipment interfaces, process technologies and business rules, the actual physical wharf is replaced to be in butt joint with a TOS, the wharf production operation condition under the drive of the TOS is displayed through a graphical interface, meanwhile, production process data are collected, stored and analyzed, and the TOS production efficiency is automatically evaluated. The method is applied to a wharf digital simulation platform, and as shown in fig. 1, the method comprises the following steps:
step S101, determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system TOS, and controlling the target simulation equipment to execute the target task at a specified double speed according to the task execution logic.
In this embodiment, when not evaluating the performance of TOS, TOS connects the physical reality pier and controls the physical reality pier. A digital simulation platform of the wharf is constructed in advance according to a GIS geographic information model, an equipment geometric and physical model, a process technology and a business rule model of the physical reality wharf, the digital simulation platform of the wharf simulates a data interface of equipment in the whole scene, and the whole elements, the whole process and the whole rule of the production of the physical reality wharf are cloned in a digital world 1.
When the performance of the TOS needs to be evaluated, a user inputs an evaluation instruction, the TOS is in butt joint with the wharf digital simulation platform, the TOS determines a virtual simulation operation plan according to the evaluation instruction, and the virtual simulation operation plan can be an operation plan virtually arranged by the user or a real historical plan task. The TOS issues a scheduling instruction to a wharf digital simulation platform according to the virtual simulation operation plan, the wharf digital simulation platform analyzes the scheduling instruction and determines target simulation equipment (such as a truck, a gantry crane or a bridge crane), target tasks (such as transporting N containers from a point A to a point B) and task execution logic (namely business process and rules), and then the target simulation equipment is controlled to execute the target tasks at a specified speed according to the task execution logic.
In this embodiment, the clock of the digital simulation platform of the wharf is adjusted based on the clock synchronization technology, so that the clock is consistent with the time of the clock source in the TOS or the deviation is limited to a sufficiently small range. Specifically, the specified multiple speed can be preset, the flow speed of the target simulation equipment during the execution of the target task can be synchronous with the specified multiple speed, the scene running is shown to be accelerated, the whole operation time (relative to a clock source in the TOS) can be reduced according to the specified multiple speed, and when the task execution time and a time node are fed back to the TOS system, the operation time needs to be multiplied by the corresponding specified multiple speed. Therefore, the accurate prejudgment of the TOS scheduling algorithm on the task execution time can be ensured while the simulation operation time is shortened, and a scheduling decision which is closer to that in the actual production operation process can be made.
Optionally, the designated multiple speed includes 1 multiple speed, or 2 multiple speed, or 4 multiple speed, or 8 multiple speed, and those skilled in the art may set other designated multiple speeds according to actual needs, which does not affect the protection scope of the present application.
For reliable reception of the scheduling instruction, in some embodiments of the present application, before determining the target simulation device, the target task, and the task execution logic according to the scheduling instruction issued by the dock operating system TOS, the method further includes:
receiving the scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
In this embodiment, the digital simulation platform of the wharf receives the scheduling instruction by using a data table stored in an open-source high-performance key-value database Redis, where the data table includes a container table, an equipment table, a shoreline work point and work queue table, and an instruction table, and stores data such as container data, equipment data, a cabin diagram, shoreline work point and work queue data, and instruction data sent by the TOS.
To improve security, in some embodiments of the present application, the TOS establishes a connection with the digital simulation platform of the quay based on connecting a first IP address and disconnecting a second IP address, and the TOS establishes a connection with the physical reality quay based on connecting the second IP address and disconnecting the first IP address.
In the embodiment, for TOS, secondary interface adaptation development is not needed, the wharf digital simulation platform can be used only by switching the IP address, production is not interfered, and TOS evaluation test cost is reduced.
And S102, displaying the execution process of the target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding simulation data in the execution process back to the TOS in real time so that the TOS updates an instruction database in real time.
In the embodiment, after the execution process of the target task is processed based on the preset three-dimensional graph rendering algorithm, the execution process can be displayed on a graphical interface, and the display form comprises real-time output of a high-fidelity and high-resolution production simulation operation scene and related operation process efficiency statistical data so as to guide a user to quickly locate the problem. The production simulation operation scene can be presented through a three-dimensional virtual environment, and the performance statistical data of the operation process can be expressed in the form of characters or two-dimensional diagrams.
In order to enable the TOS to update the instruction database in real time so as to accurately generate a next scheduling instruction in the virtual simulation operation plan, the dock digital simulation platform feeds simulation data in the execution process back to the TOS in real time, and therefore a production closed loop of 'task issuing (TOS) - > task execution (dock digital simulation platform) - > feedback state (dock digital simulation platform) - > task updating (TOS)' of the physical dock is simulated.
In order to reliably feed the simulation data back to the TOS in real time, in some embodiments of the present application, the simulation data in the execution process is fed back to the TOS in real time, which specifically includes:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the execution data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, a device state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
In this embodiment, the Kafka platform serves as a message middleware, the dock digital simulation platform pushes simulation data to the Kafka platform, and the TOS acquires the simulation data by subscribing on the Kafka platform.
It should be noted that the scheme of the above embodiment is only a specific implementation scheme provided by the present application, and other ways of feeding back the simulation data in the execution process to the TOS in real time all belong to the protection scope of the present application.
And step S103, when the target task is executed, determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process.
In this embodiment, the digital simulation platform of the dock collects data of a preset evaluation index in real time during execution, and determines an evaluation result of the efficiency of the TOS according to the collected data of the preset evaluation index when the target task is executed.
Optionally, the preset evaluation index includes one or more of a total production capacity index, a gantry crane operation index, a bridge crane operation index, a container truck (i.e., container truck) operation index, a ship operation index, a yard index, and a safety index.
In order to improve the accuracy of the evaluation result, in some embodiments of the present application, the evaluation result of the TOS performance is determined according to the collected data of the preset evaluation index, which specifically includes:
processing the data of the preset evaluation index into an evaluation operator based on a preset evaluation algorithm;
determining the evaluation result according to the evaluation operator and the weight of each preset evaluation index;
wherein the weight is determined after the wharf service expert evaluates the result of the historical simulation evaluation for multiple times.
In order to further improve the accuracy of the evaluation, in some embodiments of the present application, before determining the evaluation result of the TOS performance according to the data of the preset evaluation index in the execution process, the method further includes:
constructing a correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation focus point;
determining the preset evaluation index based on the correlation mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scoring.
In this embodiment, a correlation mapping between the TOS performance and the valid data is constructed according to a preset TOS system algorithm optimization objective and a preset evaluation focus, and the preset evaluation index is determined based on the correlation mapping.
And the wharf service expert scores the results of multiple historical simulation evaluations, and the results are used as a basis for adjusting the weights of all the statistical indexes.
By applying the technical scheme, the target simulation equipment, the target task and the task execution logic are determined according to a scheduling instruction issued by a wharf operating system TOS, and the target simulation equipment is controlled to execute the target task at the specified double speed according to the task execution logic; displaying an execution process of a target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding simulation data in the execution process back to the TOS in real time so that the TOS can update an instruction database in real time; when the target task is executed, determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process; the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a process technology and a business rule model of a physical reality wharf under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user, so that efficiency, accuracy and safety of performance evaluation of the wharf operating system are improved.
In order to further explain the technical idea of the present invention, the technical solution of the present invention is now described with reference to specific application scenarios.
The embodiment of the application provides a wharf operating system performance evaluation method, which is applied to a wharf digital simulation platform, and as shown in fig. 2 and fig. 3, the method includes the following steps:
and S1, constructing a digital simulation platform of the wharf.
A digital simulation platform of the container terminal is constructed based on a GIS geographic information model, a device geometric and physical model, a process technology and a business rule model of the container terminal, the constructed digital simulation platform simulates a data interface of equipment in a whole scene, and the whole elements, the whole process and the whole rule of the physical terminal production are cloned in a digital world 1.
The GIS geographic information model is used as a position reference when the landform of the wharf is constructed, the consistency of the digital virtual wharf and the real wharf in relative positions such as size, infrastructure and the like is ensured, and optionally, the GIS geographic information model comprises a landform surface, a range surface, a sea surface, a traffic and affiliated facility surface, a container position note point, a road marking line and the like.
The equipment geometric model is used as a direct object of TOS scheduling, a three-dimensional geometric model needs to be designed based on an accurate design drawing of the equipment, and the model can be flexibly called and adjusted during subsequent simulation scenario editing. Dynamic elements of the plant geometry model include, but are not limited to: bridge crane, gantry crane, internal truck, external truck, unmanned truck, ship, etc. In a specific application scenario of the application, the dynamic elements should construct a three-dimensional model according to a three-dimensional size, the grid precision of the three-dimensional model is not lower than 0.1m, and the model at least comprises information such as a normal line, a material, an illumination map and the like.
The device physics model is used as a bottom algorithm core for driving dynamic element motion, the device physics model needs to establish a kinematics and dynamics characteristic model of devices such as an internal and external card concentrator, an unmanned card concentrator, a gantry crane, a bridge crane and a ship, and simulates kinematics and dynamics change rules of the devices under the conditions of different loads, road conditions, operation stages and the like according to the structural characteristics of the devices, so that key parameter indexes of the devices such as running, turning, sling motion, suspension arm motion, cart motion, trolley motion, energy consumption and the like can be simulated.
The process technology and business rule model abstracts the complex wharf production process flow into a multi-agent process network. Firstly, according to the physical attributes of various devices of the wharf, a device attribute and real-time device state database is established, and single devices (hoisting devices, transportation devices and the like) in the process are abstracted into a device single model. And establishing an upstream and downstream connection relation of the equipment according to the process flow, and performing modeling of the process technology and the business rules by integrating conditions such as equipment configuration, equipment state, process sequence, connection relation, start and stop nodes, business rules and the like. The process flows can guide the flow control of the equipment, provide a basis for analyzing the instruction and are an important reference for subsequent simulation driving.
1, cloning means that a GIS (geographic information System) geographic information model, an equipment geometric and physical model, a process technology and a business rule model of the container terminal are all built strictly according to geographic mapping data, equipment drawings, a container circulation sequence, a terminal traffic network and the like of a physical reality terminal, and the time-space consistency of the simulation operation and the actual operation of the business process is ensured to the greatest extent.
The TOS is mainly responsible for making a production plan and managing operation tasks, the wharf digital simulation platform receives the TOS system operation tasks, dispatches the whole-field production equipment to execute the tasks and feeds back the equipment and the instruction execution state. The digital simulation platform of the wharf has the capability of comprehensively controlling and coordinating different types of operation equipment, and efficient coordination and utilization rate improvement of wharf production equipment are achieved through a series of functional logics and intelligent algorithms.
And S2, simulating, planning and editing the digital wharf.
The wharf digital simulation platform supports a wharf simulation scenario function, and wharf map selection and equipment physical parameter setting are sequentially carried out, so that the wharf map selection and equipment physical parameter setting are close to a physical real wharf operation rule as far as possible. And setting the parameters of the business rules, such as limiting speed on different roads and verifying the influence of the change of the business rules on the production efficiency.
The wharf map provides a simulation operation reference, different wharf space sizes are different, traffic networks are different, operation rules are different, but logic of underlying business propulsion and process connection is similar. In order to improve the flexibility, the expandability and the reusability of the simulation system, a simulation deduction engine at the bottom layer is used as a shared module, individual elements of different wharfs are packaged in a wharf map, and the wharf map can improve the efficiency of accessing a subsequent new wharf into the simulation system.
The device physics model comprises device kinematics and dynamics characteristic models such as an internal and external card collection, an unmanned card collection, a gantry crane, a bridge crane and a ship, and simulates kinematics and dynamics change rules of the device under the conditions of different loads, road conditions, operation stages and the like according to the structural characteristics of the device, so that key parameter indexes such as running, turning, hanger movement, suspension arm movement, cart movement, trolley movement, energy consumption and the like of the device can be simulated. The physical parameters directly influence the motion performance of the virtual equipment, and whether the setting of the physical parameters reasonably and directly influences the simulation precision.
And S3, directly connecting the TOS with the wharf digital simulation platform.
Two data paths exist between the TOS and the wharf digital simulation platform. One is a dispatching instruction issuing path, and the TOS issues the dispatching instruction to the wharf digital simulation platform in real time; the second one is an instruction execution state uploading path, and the wharf digital simulation platform feeds back the device position and the execution state (starting, execution and completion) of the instruction to the TOS.
The information interaction format between the wharf digital simulation platform and the TOS adopts a Json format, and both systems use a Json standard parser to parse the information. The digital simulation platform of the wharf receives a dispatching control instruction through a container table, an equipment table, an instruction table, a working point table and a working queue table stored in a Redis database, and generates corresponding equipment at a specified position according to appointed logic. Using Kafka as the messaging middleware, the device runs data in real time, machine command validation and machine hugging information, presence box information is pushed by the dock digital simulation platform to Kafka, and TOS acquires these data through subscription.
The development of the wharf digital simulation platform data interface complies with the standard that the physical reality wharf interacts with the TOS, and normal communication can be carried out on the basis that the secondary development is not carried out on the TOS. That is, as compared to the TOS, the interface with the digital simulation platform of the dock or the physical reality dock has no difference in communication mode, and only the communication address (such as the IP address) is switched.
And S4, controlling a production simulation process.
The wharf digital simulation platform analyzes the scheduling instruction received from the TOS, converts the scheduling instruction into a service scheduling logic, and then drives corresponding equipment to execute a production task according to a service flow and rules, such as transporting the specified container from an initial position to a target position. In the task execution process, the wharf digital simulation platform feeds back the instruction execution state to the TOS in real time, and the instruction database of the TOS is triggered to be updated in real time. A production closed loop of ' task issuing (TOS) ' > task execution (dock digital simulation platform) ' > feedback state (dock digital simulation platform) ' > task updating (TOS) ' of a real physical dock is simulated.
In addition, when data are interacted between the TOS system and the wharf digital simulation platform in real time, the wharf digital simulation platform can solve the problem of clock synchronization, appoint a time driving step length, support a super real-time simulation acceleration function, support 1, 2, 4 and 8 times speed production operation simulation, and greatly shorten the production operation time.
The dock digital simulation platform is also provided with a three-dimensional graphic rendering module, outputs a high-fidelity and high-resolution production simulation operation scene in real time and is used for guiding a user to quickly position.
The simulation operation scene shows the process that the wharf digital simulation platform transports the containers from the point A (initial position) to the point B (destination position) according to the TOS operation plan. Particularly relates to production operation connection of three major types of equipment, namely a gantry crane for picking and placing containers in a storage yard, a horizontal transport vehicle (a truck or an AGV) for transporting the containers on a road, and a bridge crane for taking the containers off the vehicles and loading the containers on a ship or unloading the containers from the ship to the transport vehicles.
And S5, managing and storing the production data.
The embedded data management and storage module of the wharf digital simulation platform has the capability of managing simulation state data and can manage the state data of each simulation entity in an ideal process. For example, the device operation status data includes operation, standby, offline, etc., and the instruction execution status data includes in-execution, completed, execution exception, etc. In the simulation operation process, the data management and storage module carries out mining processing, dimension normalization processing, expert experience quantification processing, result data storage and other operations on simulation data.
The hardware part of the data management and storage module comprises a data storage server and a disk array, and the data management and storage module and the disk array are automatically and respectively stored according to structured data and unstructured data. The data management and storage module software part comprises a basic database, a process database, a result database, a display model database, a knowledge base, a geographic information base, a business system management base, database management software and the like.
And S6, evaluating the production efficiency.
An efficiency evaluation module is embedded in the digital simulation platform of the wharf, and in the operation process, the efficiency evaluation module can optimize targets and evaluate side points according to a TOS algorithm, construct correlation mapping between production efficiency of the container wharf and simulation process data and equipment performance parameters, and form an index system which can be collected and quantized by a system.
After the simulation operation is finished, the dock digital simulation platform can comprehensively perform multi-dimensional evaluation on the production efficiency of the TOS algorithm according to the simulation optimization purpose and the aspects of data of the digital simulation dock, such as throughput, production efficiency, operation efficiency, energy consumption, anti-interference capacity and the like.
The evaluation indexes adopted in the method comprise:
(1) The total production capacity index is as follows: total standard box, operation time, operation efficiency and total energy consumption;
(2) Gantry crane index: average stand-alone efficiency, average idle time, fixed-point workload, moving frequency, average single-box time, execution instruction timeliness, average stand-alone energy consumption and street crossing frequency;
(3) The indexes of the bridge crane are as follows: average single machine efficiency, average idle time, average single box time, average single machine energy consumption and single-channel card collection quantity;
(4) The card collection index: turnover rate, waiting idle time for arriving at an operation box area, waiting idle time for a shore bridge, idle load rate, average driving speed, waiting for oiling/average charging time in a queuing way, command change response timeliness and average energy consumption;
(5) The ship indexes are as follows: single machine efficiency, ship time efficiency, on-berth efficiency, stock yard rollover rate, overhead/staging rate.
(6) The yard index is as follows: equipment resource proportion, the single-berth same-ship box volume of a storage yard and the busyness of site operation instructions.
(7) The safety index is as follows: accident frequency, dangerous case frequency and storage yard box placing deviation.
Through applying above technical scheme, compare in prior art, have following beneficial effect:
1. the digital simulation platform of the wharf integrates a GIS geographic information model, a device geometry and physics model, a process technology and a business rule model of a physical reality wharf at the same time, can simulate a full-scene device data interface, and really realizes personalized customization according to the physical reality wharf 1. For a wharf operating system, secondary interface adaptation development is not needed, the wharf digital simulation platform can be used only by switching IP addresses, production is not interfered, efficiency evaluation cost of TOS is reduced, evaluation is performed in a virtual digital space, and safety and zero risk are achieved.
2. The method can evaluate the production efficiency from multiple areas of the wharf overall situation, the land side and the sea side, can perform multi-dimensional analysis from the perspective of a single production device, covers the production efficiency, the operation efficiency, the energy consumption and the anti-interference capability in the evaluation range, and has the overall comprehensive analysis capability from the macro to the micro and from the local. The completeness of the evaluation data is far greater than that of the real-time production evaluation test.
3. When data are interacted between the TOS and the wharf digital simulation platform in real time, the wharf digital simulation platform can solve the problem of clock synchronization, appoint a time driving step length, support a super real-time simulation acceleration function, support 1, 2, 4 and 8 times speed production operation simulation, and greatly shorten the duration of an evaluation test process.
The embodiment of the present application further provides a digital simulation platform for a dock, as shown in fig. 4, the platform includes:
the simulation management module 100 is configured to determine a target simulation device, a target task, and a task execution logic according to a scheduling instruction issued by the wharf operating system TOS, and control the target simulation device to execute the target task at a specified multiple speed according to the task execution logic;
the display module 200 is used for displaying the execution process of the target task in real time based on a preset three-dimensional graph rendering algorithm;
a feedback module 300, configured to feed back simulation data in the execution process to the TOS in real time, so that the TOS updates the instruction database in real time;
the performance evaluation module 400 is configured to determine an evaluation result of the TOS performance according to data of a preset evaluation index in an execution process when the target task is executed;
the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a process technology and a business rule model of a physical reality wharf under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user.
In a specific application scenario of the present application, as shown in fig. 3, the functions of the emulation management module include clock synchronization, process control, data management, and emulation playback. The function of the efficiency evaluation module comprises evaluation index management and index empowerment calculation.
In a specific application scenario of the present application, the platform further includes:
the Redis analysis module is used for receiving a scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
In a specific application scenario of the present application, the feedback module (e.g., KAFKA processing module in fig. 3) is specifically configured to:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the execution data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, a device state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
In a specific application scenario of the present application, as shown in fig. 3, the KAFKA processing module is configured to upload truck data, gantry crane data, bridge crane data, and simulation control data.
In a specific application scenario of the present application, the platform further includes a data management and storage module, integrated in the simulation management module, and configured to:
constructing correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation emphasis point;
determining the preset evaluation index based on the association mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scores.
In a specific application scenario of the present application, as shown in fig. 3, the platform further includes:
the port management module is used for carrying out shore line management, storage yard management, card collection management and message management;
the human-computer interaction module is used for carrying out UI management, scene browsing management and simulation scenario editing;
the algorithm module is used for calculating lane selection and manual instruction selection;
the exception management module is used for storing exception logs and giving an exception prompt and an alarm;
the digital wharf base comprises a three-dimensional rendering module and a GIS module and is used for providing an algorithm for graphic rendering and coordinate unification;
the device comprises a man-machine interaction module, an algorithm module, an exception management module, a simulation management module, a feedback module and an efficiency evaluation module, wherein the man-machine interaction module, the algorithm module, the exception management module, the simulation management module, the feedback module and the efficiency evaluation module are respectively connected with a port management module, a display module is integrated in the man-machine interaction module, and a digital wharf base is the bottom layer of a wharf digital simulation platform.
In a specific application scenario of the present application, as shown in fig. 3, the port management module includes:
the shore line management module is used for carrying out bridge crane management and ship management;
the storage yard management module is used for carrying out gantry crane management and container management;
the card collecting management module is used for carrying out unmanned card collecting management and manned card collecting management;
and the message registration center is used for performing message registration and message management.
The propulsion of each instruction task and the recording of key event nodes in the port management module are all based on process control and data management algorithms provided by the simulation management module, and a clock synchronization algorithm embedded in the simulation management module can be used for accelerating the running of a simulation process.
In a specific application scenario of the present application, as shown in fig. 3, the three-dimensional rendering module includes a static element rendering module, a dynamic element rendering module, a weather illumination rendering module, and a seawater system rendering module.
In a specific application scenario of the present application, as shown in fig. 3, the GIS module is configured to perform shp analysis processing, projection coordinate conversion, bin/bay coordinate conversion query, shore line coordinate conversion, ship bay coordinate query, and bridge/dragon exchange point coordinate query.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application 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; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (8)
1. A wharf operating system performance evaluation method is applied to a wharf digital simulation platform, and comprises the following steps:
determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system (TOS), and controlling the target simulation equipment to execute the target task at a specified speed according to the task execution logic;
displaying the execution process of the target task in real time based on a preset three-dimensional graph rendering algorithm, and feeding back simulation data in the execution process to the TOS in real time so that the TOS updates an instruction database in real time;
when the target task is executed, determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process;
the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a flow process and a business rule model of a physical reality wharf under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user;
before determining an evaluation result of the TOS performance according to the data of the preset evaluation index in the execution process, the method further includes:
constructing a correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation focus point;
determining the preset evaluation index based on the association mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scores.
2. The method of claim 1, wherein prior to determining the target simulation device, the target task, and the task execution logic based on a scheduling instruction issued by a Terminal Operating System (TOS), the method further comprises:
receiving the scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
3. The method of claim 1, wherein the simulation data during execution is fed back to the TOS in real time, specifically:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the simulation data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, a device state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
4. The method of claim 1, wherein the TOS establishes the connection with the digital simulation platform of the quay based on connecting a first IP address and disconnecting a second IP address, the TOS establishing the connection with the physical reality quay based on connecting the second IP address and disconnecting the first IP address.
5. A dock digital simulation platform, the platform comprising:
the simulation management module is used for determining target simulation equipment, a target task and task execution logic according to a scheduling instruction issued by a wharf operating system (TOS), and controlling the target simulation equipment to execute the target task at a specified multiple speed according to the task execution logic;
the display module is used for displaying the execution process of the target task in real time based on a preset three-dimensional graphic rendering algorithm;
the feedback module is used for feeding back simulation data in the execution process to the TOS in real time so that the TOS can update the instruction database in real time;
the efficiency evaluation module is used for determining an evaluation result of the TOS efficiency according to data of a preset evaluation index in the execution process when the target task is completely executed;
the wharf digital simulation platform is constructed according to a GIS geographic information model, an equipment geometric and physical model, a flow process and a business rule model of a physical reality wharf under the TOS, and the scheduling instruction is generated by the TOS according to a virtual simulation operation plan corresponding to an evaluation instruction input by a user;
the platform also comprises a data management and storage module, which is integrated with the simulation management module and is used for:
constructing a correlation mapping between the TOS efficiency and the simulation data according to a preset TOS system algorithm optimization target and a preset evaluation focus point;
determining the preset evaluation index based on the association mapping;
and each preset evaluation index is provided with a weight determined according to expert experience scores.
6. The platform of claim 5, wherein the platform further comprises:
the Redis analysis module is used for receiving the scheduling instruction through a data table stored in a Redis database;
the data table comprises a container table, an equipment table, a shoreline working point and working queue table and an instruction table.
7. The platform of claim 5, wherein the feedback module is specifically to:
pushing the simulation data to a Kafka platform, and feeding the simulation data back to the TOS in real time based on the Kafka platform;
the simulation data comprises one or more of a receiving instruction queue, an optimal instruction message, an execution state message, an equipment state message, an instruction confirmation message, an instruction completion message, a path planning message and a simulation rate message.
8. The platform of claim 5, wherein the platform further comprises:
the port management module is used for carrying out shore line management, storage yard management, card collection management and message management;
the human-computer interaction module is used for carrying out UI management, scene browsing management and simulation scenario editing;
the algorithm module is used for calculating lane selection and manual instruction selection;
the abnormity management module is used for storing an abnormity log and giving an abnormity prompt and alarm;
the digital wharf base comprises a three-dimensional rendering module and a GIS module and is used for providing an algorithm for graphic rendering and coordinate unification;
the human-computer interaction module, the algorithm module, the abnormity management module, the simulation management module, the feedback module and the efficiency evaluation module are respectively connected with the port management module, the display module is integrated with the human-computer interaction module, and the digital wharf base is the bottom layer of the wharf digital simulation platform.
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