CPC G06Q 10/06311 (2013.01) | 3 Claims |
1. A method for constructing a locomotive collaborative transportation scheduling system based on cyber-physical fusion, comprising:
step 1, planning an actual site location where a device is located based on an actual physical environment on site; wherein in step 1, the number and locations of the physical devices required for locomotive transportation are planned based on the actual physical environment on site of the locomotive transportation, and the physical devices comprises signal lights, switch machines, and measurement and control substations;
step 2, planning a connection mode and an information transmission path of the device according to the actual site location of the device, and constructing a distributed cyber-physical system collaborative architecture based on cyber-physical system;
wherein the specific process of step 2 is as follows:
connecting signal lights and switch machines with the nearest measurement and control substations through the locations of the physical devices on site, wherein a connection mode is star connection; planing an device connection mode and an information transmission path; applying the cyber-physical system theory to establish a distributed structure for an interaction between a information layer and a physical layer of terminals of the locomotive collaborative transportation scheduling cyber-physical s stem to build compositions and functions of the information layer and the physical layer; researching a information process that each terminal processor needs to exchange and transmit based on a functional requirement of different physical devices, and building an information interaction model; wherein the physical layer of the cyber-physical system is actual physical devices controlled by the controller in the system and a communication network connecting these physical devices, the actual physical devices comprise signal lights, switch machines, and measurement and control substations; the communication network is a hybrid network combining ring networks and star networks; each device in the physical layer of the cyber-physical system is equipped with a physical transmission port for information interaction with other physical devices, which is responsible for realizing actual physical behaviors of the system; the information layer of the cyber-physical system comprises a data center and a plurality of communication nodes, the information layer of the cyber-physical system consists of a plurality of virtual physical devices realized by the actual physical devices through real-time multitasking programming and the information transmitted by each device; and the information layer of the cyber-physical system is configured to process and transmit various information in the system and generate corresponding information transmission content, which is responsible for implementing information interaction between the physical devices in the system;
forming the edge computing groups composed of the measurement and control substations and their subordinate signal lights and switch machines according to a structure of the locomotive collaborative transportation scheduling cyber-physical system, wherein the edge computing groups exchange information through the backbone network, and a plurality of the measurement and control substations achieve information coordinated control of a plurality of controllers;
building the collaborative architecture of the cyber-physical system of a coal mine underground locomotive collaborative transportation scheduling, wherein the collaborative architecture comprises an application layer, a cloud data layer, a backbone network layer, a local network layer and a physical layer; wherein the application layer comprises a monitoring center and a control center; the cloud data layer comprises the cloud data processing center; the backbone network layer comprises a plurality of switch machines connected through ethernet; the local network layer comprises a data processing center, a measurement and control substation, a controller local area network communication a positioning base station, and an ultra wideband wireless carrier communication; the physical layer comprises an execution device, a sensing device, and an onboard device; the measurement and control substation conducts interactive communication with the executive device and the sensing device subordinated through the star network composed of the controller local area network communication, the positioning base station receives data information of the onboard device through the ultra wideband wireless carrier communication; and different measurement and control substations or positioning base stations exchange information through an ethernet ring network composed of switch machines, and transmit information in the cloud data center;
step 3, describing an information transmission relationship between physical devices in a matrix manner based on a cyber-physical system collaboration architecture and an information transmission path between the physical devices, and constructing an information collaboration computing model;
wherein, a network directed graph is used to construct the information collaboration computing model in step 3, the network directed graph describes a communication relationship between system device controllers, and edges in the network directed graph represent a direction of information flow between the physical devices;
there are m of edge devices in an edge computing group, a network node splitting method is used to split nodes, the number of network vertices is 2m, an information adjacency matrix T′=[aij]2m×2m between the vertices is constructed according to two split vertices v′ and v″, wherein aij is an adjacency relationship between vertices, when information flows from a vertex i to a vertex j, aij is 1, otherwise aij is 0;
in the edge computing group, there are still n of non-split network nodes, information of the edge devices flows from the vertices v″ to the non-split network nodes, and information of the non-split network nodes flows from the vertices v′ of the edge devices;
building a full information adjacency matrix T of the edge computing group as following:
wherein, m′ represents the number of edge devices of the vertices v′ after using the network node splitting method, m″ represents the number of edge devices of the vertices v″ after using the network node splitting method, Tm′×m′ represents a matrix module between split vertices v′ and split vertices v′, Tm′×m″ represents a matrix module between the split vertices v′ and the split vertices v″, Tm′×n represents a matrix module between the split vertices v′ and the non-split network nodes, Tm″×m′ represents a matrix module between the split vertices v″ and the split vertices v′, Tm″×m″ represents a matrix module between the split vertices v″ and the split vertices v″, Tm′×n represents a matrix module between the split vertices v″ and the non-split network nodes, Tn×m′ represents a matrix module between the non-split network nodes and the split vertices v′, Tn×m″ represents a matrix module between the non-split network nodes and the split vertices v″, and Tn×n represents a matrix module between the non-split network nodes;
the matrix of the information collaboration computing model in step 3 is to use the full information adjacency matrix of the edge computing group as a sub module to be called in the full information adjacency matrix of the system, a data center on the cloud realizes a collaborative computing of an entire network system by calling an edge computing group information collaborative computing sub module, the edge computing group information collaborative computing sub module realizes the collaborative computing between the edge computing groups, and the process includes the following steps:
unified numbering of network nodes of the edge computing group under system information collaboration; specifically, in the case of multiple edge computing groups, the network nodes of different edge computing groups are numbered uniformly in the system; supposing that network nodes in an edge computing group 1 are numbered from 1 to p, wherein there are m1 of split nodes and n1 of non-split nodes; network nodes of an edge computing group 2 are numbered from p+1 to p+q, wherein there are m2 of split nodes and n2 of non-split nodes;
constructing the information adjacency matrix between edge computing groups under system information collaboration; specifically, the information adjacency matrix between edge computing groups is Z, and the information adjacency matrix Z12 between the edge computing group 1 and the edge computing group 2 in Z is:
wherein, m′1 represents the vertex v′ of the edge computing group 1 after splitting, m′2 represents the vertex v′ of the edge computing group 2 after splitting, m″1 represents the vertex v″ of the edge computing group 1 after splitting, m″2 represents the vertex v″ of the edge computing group 2 after splitting; Z12m′1×m′2 represents a matrix module between the vertex v′ of the edge computing group 1 after splitting and the vertex v′ of the edge computing group 2 after splitting, Z12m′1×m″2 represents a matrix module between the vertex v′ of the edge computing group 1 after splitting and the vertex v″ of edge computing group 2 after splitting, Z12m′1×n2 represents a matrix module between the vertex v′ of the edge computing group 1 after splitting and the non-split nodes of the edge computing group 2, Z12m″1×m′2 represents a matrix module between the vertex v″ of the edge computing group 1 after splitting and the vertex v′ of the edge computing group 2 after splitting, Z12m″1×m″2 represents a matrix module between the vertex v″ of the edge computing group 1 after splitting and the vertex v″ of the edge computing group 2 after splitting, Z12m″1×n2 represents a matrix module between the vertex v″ of the edge computing group 1 after splitting and the non-split nodes of the edge computing group 2, Z12n1×m′2 represents a matrix module between the non-split nodes of the edge computing group 1 and the vertex v′ of the edge computing group 2 after splitting, Z12n1×m′2 represents a matrix module between the non-split nodes of the edge computing group 1 and the vertex v″ of the edge computing group 2 after splitting, and Z12n1×n2 represents a matrix module between the non-split nodes of the edge computing group 1 and the non-split nodes of the edge computing group 2;
constructing the full information adjacency matrix of the whole locomotive cooperative transportation scheduling system under the system information collaboration; a construction process of an unified computing model of a whole cloud-side locomotive network system is as follows: conducting node processing to a cloud data center through the network node splitting method, the cloud data center is regarded as the edge computing group with only one controller, and all the edge computing groups in the system are obtained as the full information adjacency matrix W of the system according to the methods of equations (1) and (2), as shown in equation (3);
wherein, Z represents an information adjacency matrix between the edge computing groups, k represents the total number of edge computing groups after removing the cloud data center in the system, k+1 represents the cloud data center of the system; T1 represents a full information connection matrix of the edge computing group 1, T2 represents a full information connection matrix of the edge computing group 2; Tk+1 represents a full information connection matrix of a cloud data processing center; Z12 represents an information connection matrix between the edge computing group 1 and the edge computing group 2, Z21 represents an information connection matrix between the edge computing group 2 and the edge computing group 1; Z(k+1)1 represents an information connection matrix between the cloud data center of the system and the edge computing group 1, Z1(k+1) represents an information connection matrix between the edge computing group 1 and the cloud data processing center; Z2(k+1) represents an information connection matrix between the edge computing group 2 and the cloud data processing center; and Z(k+1)2 represents an information connection matrix between the cloud data processing center and the edge computing group 2;
step 4, analyzing data space and execution time required for program operation according to a device function implementation program, analyzing an information communication interface and an information transmission delay required by a controller according to a collaboration architecture of the cyber-physical system and information interaction contents between the physical devices; selecting a matching controller type based on a maximum data space and an execution time required for the program operation, the information communication interface and the information transmission delay, combined with real-time and reliability required by the locomotive cooperative transportation scheduling system;
step 5, writing a controller function scheduling program in combination with a locomotive scheduling strategy to complete the construction of a locomotive collaborative transportation scheduling cyber-physical system, and realizing a locomotive automatic scheduling through locomotive collaborative transportation scheduling cyber-physical system.
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