CN108628322B - Reliability calculation method and device for AGV path network - Google Patents
Reliability calculation method and device for AGV path network Download PDFInfo
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Abstract
The invention discloses a method and a device for calculating the reliability of an AGV path network, wherein the method comprises the following steps: acquiring a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle; acquiring a directed multi-graph corresponding to a path network; the nodes in the directed multi-graph are track intersection points, reverse track turning points and equidirectional track lane change points, and directed edges among the nodes are tracks; determining the reliability of the path network according to the strong communication condition of the whole directed multi-graph after cutting any n directed edges; according to the method, the multi-nested annular path network is converted into the directed multi-graph, the reliability of the path network can be calculated by utilizing the connectivity calculation algorithm of the directed multi-graph, a user can conveniently and quickly judge whether the reliability index of the AGV path network meets the requirement in practice, and the efficiency of design planning is improved.
Description
Technical Field
The invention relates to the field of planning and layout of production workshops or manufacturing systems, in particular to a method and a device for calculating reliability of an AGV path network.
Background
With the high integration of plant functions, the organization of discrete customized production is gradually evolving from a process-oriented cluster to a production plant consisting of a plurality of flexible manufacturing units including robots, wherein the materials flow in substantially the same direction (e.g., roughing unit → semi-finishing unit → assembly and debugging unit). Meanwhile, a material storage and transportation system composed of Automatic Guided Vehicles (AGV) has the characteristics of high flexibility, good expandability and good maintainability, so that the AGV is suitable for being applied to unit flow workshops. In a word, for the randomly arrived individual demand orders, the unit flow production organization mode according to the large process route is combined with the intelligent workshop of the AGV material storage and transportation system, and the unbalanced distribution of the workshop logistics intensity on time and space is reduced to the maximum extent through the optimized layout, so that the material transportation and production efficiency of the workshop is improved.
In the prior art, an intelligent workshop is provided with a unit flow type production organization structure, and an important automatic material storage and transportation system corresponding to the unit flow type production organization structure often has the characteristics of a Unidirectional Guided-path Network (UGN) and containing a plurality of Automatic Guided Vehicles (AGV), wherein the path Network topological structure is a multi-nested closed ring. The AGV path of the material storage and transportation system has certain flexibility, and even if a certain AGV breaks down, the handling of the products in the whole workshop is not broken down; and the workshop can be effectively supported to adapt to the selection of processing paths of different product processes, and the length of the AGV transportation path can be properly shortened. Therefore, how to calculate the reliability of the AGV path network in the material storage and transportation system enables a user to quickly determine whether the reliability index of the AGV path network actually meets the requirement, improves the efficiency of design planning, and avoids the situation that the reliability of the AGV path network cannot guarantee the flexibility of the AGV path network and support different path selections, which is a problem that needs to be solved urgently nowadays.
Disclosure of Invention
The invention aims to provide a method and a device for calculating the reliability of an AGV path network, so as to calculate the reliability of the AGV path network and improve the efficiency of design planning.
In order to solve the above technical problem, the present invention provides a method for calculating reliability of an AGV path network, including:
acquiring a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle;
acquiring a directed multi-graph corresponding to the path network; wherein, the nodes in the directed multi-graph are the track intersection point, the reverse track turning point and the equidirectional track changing point, and the directed edges among the nodes are the tracks;
determining the reliability of the path network according to the strong communication condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1.
Optionally, when n is equal to 1, determining the reliability of the path network according to a strong connectivity condition of the whole edge-truncated directed multi-graph after any n directed edges are truncated, where the determining includes:
judging whether any 1 directed edge is cut off and whether the directed multiple graphs after the whole cut edge are strongly communicated;
if yes, determining the reliability of the path network to be 1;
and if not, determining that the reliability of the path network is 0.
Optionally, when n is 2, determining the reliability of the path network according to a strong connectivity condition of the whole edge-truncated directed multi-graph after any n directed edges are truncated, including:
judging whether any 1 directed edge is cut off and whether the directed multiple graphs after the whole cut edge are strongly communicated;
if not, determining the reliability of the path network to be 0;
if yes, judging whether any 2 directed edges are cut off and whether the directed multiple graphs after the edges are cut off are strongly communicated;
if not, determining the reliability of the path network to be 1;
and if so, determining the reliability of the path network to be 2.
Optionally, the determining whether to cut any 1 directed edge and the whole directed multi-graph are strongly connected includes:
numbering all the directed edges in the directed multi-graph, and taking the minimum number as the current number;
cutting a directed edge corresponding to the current number from the directed multi-graph, and calculating a strongly-connected component of the cut directed multi-graph by using a preset algorithm;
judging whether the directed multi-graph after the whole edge cutting is strongly connected or not according to the strongly connected component;
if not, executing the step of determining that the reliability of the path network is 0;
if so, judging whether the current number is the maximum number or not;
if the current number is not the maximum number, taking the next number as the current number, executing the step of cutting a directed edge corresponding to the current number in the directed multi-graph, and calculating a strongly-connected component of the directed multi-graph after edge cutting by using a preset algorithm;
and if the current number is the maximum number, executing the step of judging whether any 2 directed edges are cut off and the directed multi-graph after the whole edge is cut off is strongly communicated.
Optionally, the method further includes:
and if the directed multi-graph after the whole edge cutting is not strongly communicated, outputting the directed edge corresponding to the current number and two nodes connected with the directed edge corresponding to the current number.
Optionally, after the obtaining of the path network of the automatic guided vehicle, the method includes:
judging whether the number of the corresponding tracks of each discharge port and each feed port in the path network is more than or equal to 2;
if yes, executing the step of obtaining the directed multiple graph corresponding to the path network;
if not, outputting the corresponding tracks of which the number is less than 2 of the discharge port and the feed port, and connecting the track intersection point, the reverse track turning point or the equidirectional track changing point.
In addition, the present invention also provides a reliability calculation device for an AGV path network, including:
the first acquisition module is used for acquiring a path network of the automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle;
the second acquisition module is used for acquiring the directed multiple graph corresponding to the path network; wherein, the nodes in the directed multi-graph are the track intersection point, the reverse track turning point and the equidirectional track changing point, and the directed edges among the nodes are the tracks;
the determining module is used for determining the reliability of the path network according to the strong connection condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1.
Optionally, when n is equal to 1, the determining module includes:
the first determining submodule is used for judging whether any 1 directed edge is cut off and whether the directed multi-graph after the whole edge is cut off is strongly communicated; if yes, determining the reliability of the path network to be 1; and if not, determining that the reliability of the path network is 0.
Optionally, when n is 2, the determining module includes:
the second determining submodule is used for judging whether any 1 directed edge is cut off and whether the whole directed multi-graph after the edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 0; if yes, sending a starting signal to a third determining submodule;
the third determining submodule is used for judging whether any 2 directed edges are cut off and the directed multi-graph after the whole edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 1; and if so, determining the reliability of the path network to be 2.
Optionally, the apparatus further comprises:
the judging module is used for judging whether the number of the corresponding tracks of each discharge port and each feed port in the path network is more than or equal to 2; if yes, sending a starting signal to the second acquisition module; if not, sending a starting signal to the output module;
the output module is used for outputting the corresponding tracks of the discharge port and the feed port, the number of the corresponding tracks of which is less than 2, and the track junction, the reverse track turning point or the equidirectional track changing point which are connected with the corresponding tracks.
The invention provides a reliability calculation method of an AGV path network, which comprises the following steps: acquiring a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle; acquiring a directed multi-graph corresponding to a path network; the nodes in the directed multi-graph are track intersection points, reverse track turning points and equidirectional track lane change points, and directed edges among the nodes are tracks; determining the reliability of the path network according to the strong communication condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1;
therefore, the method and the device can utilize the connectivity calculation algorithm of the directed multi-graph to calculate the reliability of the path network by converting the multi-nested annular path network into the directed multi-graph, facilitate a user to quickly judge whether the reliability index of the AGV path network meets the requirement in practice, and improve the efficiency of design planning. In addition, the invention also provides a reliability calculation device of the AGV path network, and the reliability calculation device also has the beneficial effects.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flowchart illustrating a method for calculating reliability of an AGV path network according to an embodiment of the present invention;
FIG. 2 is a diagram of a path network topology of an automated guided vehicle according to another method for calculating the reliability of an AGV path network according to an embodiment of the present invention;
FIG. 3 is a directed multiple graph of an automated guided vehicle for another method of reliability calculation for an AGV path network according to an embodiment of the present invention;
FIG. 4 is a flowchart of another AGV path network reliability calculation method according to an embodiment of the present invention;
FIG. 5 is a block diagram of a reliability calculation device of an AGV path network according to an embodiment 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.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for calculating reliability of an AGV path network according to an embodiment of the present invention. The method can comprise the following steps:
step 101: acquiring a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle.
The path network of the automatic guided vehicle in this step may be a path network of a plurality of automatic guided vehicles in the material storage and transportation system, as shown in fig. 2; or may be a network of paths for an automated guided vehicle. The present embodiment does not set any limit to this.
It can be understood that the purpose of this step may be to acquire the path network of the automatic guided vehicle for the processor, and the specific acquisition mode of the path network of the automatic guided vehicle may be set by the designer according to the practical scenario and the user requirement, for example, the processor may receive the path network topology structure diagram of the Automatic Guided Vehicle (AGV) shown in fig. 2 sent by the user, and extract the path network therein; it is also possible for the processor to receive the path network of the automated guided vehicles directly from the material handling system or the automated guided vehicles. The present embodiment does not limit the path network of the automated guided vehicle as long as the processor can acquire the path network.
Specifically, as shown in fig. 2, the path network of the automated guided vehicle in this step may only include track junction points (1, 2, 3, and 4), reverse track turning points (8, 9, and 10), equidirectional track lane change points (5, 6, and 7), and tracks including the traveling direction of the automated guided vehicle; the device can also comprise a feeding port (P) and a discharging port (D) so as to conveniently judge the accessibility of the feeding port and the discharging port. The specific content of the path network of the automatic guided vehicle in this step may be set by the designer according to the practical scenario and the user requirement, which is not limited in this embodiment.
Preferably, in order to ensure the accessibility of the material inlet and the material outlet in the path network, the step may further include a step of determining whether the number of the tracks corresponding to each material outlet and each material inlet in the path network is greater than or equal to a preset number of edges, for example, determining whether the number of the tracks corresponding to each material outlet and each material inlet in the path network is greater than or equal to 2; if yes, go to step 102; if not, outputting the corresponding tracks of which the number is less than 2 of the discharge port and the feed port, and the track intersection point, the reverse track turning point or the equidirectional track changing point which are connected with the corresponding tracks, so as to inform a user when the number of the tracks corresponding to the discharge port or the feed port is less than 2, and ensuring that the number of the tracks corresponding to the discharge port or the feed port is at least 2.
Step 102: acquiring a directed multi-graph corresponding to a path network; the nodes in the directed multi-graph are track intersection points, reverse track turning points and equidirectional track lane change points, and directed edges among the nodes are tracks.
The purpose of this step may be to convert a track including the traveling direction of the automated guided vehicle in the path network into directed edges between nodes of the directed multi-graph by converting a track intersection point, a reverse track turning point, and a same-direction track changing point in the path network of the automated guided vehicle into nodes of the directed multi-graph, and obtain the directed multi-graph corresponding to the path network. The specific acquisition mode of the directed multi-graph corresponding to the path network in this step may be set by the designer, and this embodiment does not limit the specific acquisition mode as long as the directed multi-graph including the track intersection point, the reverse track u-turn point, the node corresponding to the equidirectional track change point, and the directed edge corresponding to the track in the path network can be acquired.
Specifically, the step may be that the track junction points (1, 2, 3, and 4), the reverse track turning points (8, 9, and 10), and the equidirectional track lane change points (5, 6, and 7) in fig. 2 are converted into 10 nodes (1 to 10) in fig. 3, and the track in fig. 2 is converted into directed edges between the nodes in fig. 3.
Step 103: determining the reliability of the path network according to the strong communication condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1.
It can be understood that, in this step, the reliability of the path network is determined according to the strong connectivity condition of the whole directed multi-graph after the cut of any n directed edges, and may be the reliability of the path network defined by determining the strong connectivity of the directed multi-graph after the cut of any preset number of directed edges. If any edge in the directed multi-graph is removed, if the remaining directed multi-graphs are still strongly connected, the reliability value R of the original directed multi-graph is defined to be 1, otherwise, the reliability value R is defined to be 0. If any n edges in the directed multi-graph are removed and the remaining directed multi-graphs are still strongly connected, the reliability of the original directed multi-graph is R ═ n. That is, the reliability of the path network is related to the K-edge connectivity of the corresponding directed multi-graph.
Wherein n in this step may be the maximum number of cut directed edges in the directed multi-graph. The specific value of n can be set by a designer according to a practical scene and user requirements, and if only the path network of the automatic guided vehicle needs to be determined to have the minimum flexibility, n can be set to be 1; if the maximum reliability of the path network needs to be determined, n may be set to a value obtained by subtracting 1 from the minimum number of directed edges between nodes in the directed multi-graph, and if the minimum number of directed edges between nodes in the directed multi-graph in fig. 3 is 2, any 2 directed edges in the directed multi-graph are cut off, and the directed multi-graph cannot be strongly connected all the time, that is, the reliability R of the directed multi-graph cannot be greater than or equal to 2, n may be set to 1, and it may be determined whether the reliability R of the directed multi-graph is 0 or 1.
It should be noted that, for the specific manner of determining the reliability of the path network in this step, the designer may set itself according to the practical scenario and the user requirement, if it is only necessary to determine whether the path network of the automated guided vehicle has the minimum flexibility, that is, only one edge in the directed multiple graph may be removed, and it is determined whether the remaining directed multiple graph is still strongly connected, if n is 1, it is determined whether any 1 directed edge is removed, and whether the whole directed multiple graph after edge removal is strongly connected; if yes, determining the reliability of the path network to be 1; if not, determining the reliability of the path network to be 0; if the maximum reliability of the path network needs to be determined, if the minimum number of directed edges among nodes in the directed multi-graph is 3, namely n is 2, judging whether any 1 directed edge is cut off and the whole directed multi-graph after the edge is cut off is strongly connected; if not, determining the reliability of the path network to be 0; if yes, judging whether any 2 directed edges are cut off and whether the directed multi-graph after the whole edge cutting is strongly communicated; if not, determining the reliability of the path network to be 1; and if so, determining the reliability of the path network to be 2. The present embodiment does not impose any limitation as long as the reliability of the path network can be determined.
It can be understood that the above determination method of the reliability of the path network when n is 2 is exemplified by a method of cutting off any 1 directional edge and then cutting off any 2 directional edges; or any 2 directed edges can be cut first, and then any 1 directed edge can be cut. The present embodiment does not set any limit to this.
Specifically, for the specific manner of determining whether an arbitrary n directed edges are cut off and the directed multi-graph after the entire cut edge is strongly connected, taking n equal to 1 as an example, all directed edges in the directed multi-graph corresponding to the path network may be numbered first, each directed edge is cut off in an ergodic manner according to the number, if the strong connectivity of the directed multi-graph after cutting off 1 directed edge each time is established, it may be determined that the reliability of the directed multi-graph (i.e., the original directed multi-graph) is 1 or every two directed edges are continuously cut off in an ergodic manner according to the number, otherwise, the reliability is 0. Specifically, as shown in fig. 4, the method includes:
step 201: and numbering all directed edges in the directed multi-graph, and taking the minimum number as the current number.
The minimum number in this step may be a number with the smallest numerical value among numbers corresponding to all the directed edges.
It can be understood that, in this embodiment, one directed edge of the directed multi-graph is cut through traversing from the directed edge with the smallest number, and one directed edge of the directed multi-graph may also be cut through traversing from the largest number or other numbers, as long as one directed edge of the directed multi-graph can be cut through traversing, which is not limited in this embodiment.
Step 202: and cutting the directed edge corresponding to the current number in the directed multi-graph, and calculating the strongly-connected component of the directed multi-graph after edge cutting by using a preset algorithm.
The purpose of this step may be to cut one directed edge corresponding to the current number from the complete directed multi-graph, so as to perform traversal calculation on the strongly connected component of the directed multi-graph after one directed edge in the complete directed multi-graph is cut each time.
It can be understood that the specific algorithm selection of the preset algorithm for calculating the strongly connected component of the cut-edge directed multi-graph can be set by a designer according to a practical scene and user requirements, for example, a Gabow algorithm or a Tarjan algorithm can be adopted. The present embodiment does not set any limit to this.
Step 203: judging whether the directed multi-graph after the whole edge cutting is strongly connected or not according to the strongly connected component; if not, go to step 204; if yes, go to step 205.
The purpose of this step may be to determine whether the whole edge-truncated directed multi-graph is strongly connected according to a strongly connected component of the directed multi-graph after a directed edge is truncated, which is calculated according to a preset algorithm. The specific manner of determining whether the whole edge-cut directed multi-graph is strongly connected or not may be set correspondingly according to the selected preset algorithm, as long as whether the whole edge-cut directed multi-graph is strongly connected or not may be determined according to the strongly connected component, which is not limited in this embodiment.
Step 204: the reliability of the path network is determined to be 0.
In this step, after the directed edge corresponding to the current number is cut from the directed multi-graph, when the whole directed multi-graph after the cut edge is not strongly connected, the reliability of the path network is determined to be 0.
It can be understood that, in order to facilitate the user to know the directed edge and the node that affect the reliability, this step may further include a step of outputting the directed edge corresponding to the current number and two nodes connected to the directed edge corresponding to the current number, or outputting a track intersection point, an inverse track turning point, or an equidirectional track lane change point, where the track corresponding to the current number and the track corresponding to the current number are connected. And if the directed edge of the current number is removed and the remaining directed multi-graph does not have strong connectivity any more, the directed edge is the directed edge influencing the reliability, and the two nodes connected by the directed edge are the nodes influencing the reliability.
Further, the step may further include a step of automatically adding or prompting a user to add a directed edge and/or a directed edge according to the directed edge and the node which affect the reliability, so as to improve the reliability of the AGV path network by adding the number of directed edges, and reduce weak links which affect the strong connectivity of the entire AGV path network, for example, intersection nodes between tracks (for example, increasing lane change points and turn around points) may be added, and nodes and directed edges in the directed multi-graph are correspondingly added; tracks may also be added, corresponding to the addition of directed edges connecting existing nodes in the directed multi-graph. The present embodiment does not set any limit to this.
Step 205: judging whether the current number is the maximum number or not; if not, go to step 206; if so, go to step 207.
After the directed edge corresponding to the current number is cut from the directed multi-graph, when the whole directed multi-graph after the cut edge is strongly communicated, whether the traversal of each directed edge is finished is determined by judging whether the current number is the maximum number.
Step 206: the next number is used as the current number, and the process proceeds to step 202.
In this step, when the traversal of each directed edge is not completed, the next number is used as the current number, and the traversal is continued in step 202.
Step 207: the reliability of the path network is determined to be 1.
It is to be understood that fig. 4 is presented by way of example only of determining whether the path network of the automated guided vehicle has minimal flexibility, i.e., only one edge of the directed multi-graph may be removed to determine whether the remaining directed multi-graphs are still strongly connected. Therefore, after determining that any 1 directed edge is cut off and the directed multi-graph after the whole cut edge is strongly communicated, the reliability of the path network can be directly determined to be 1 in the step. If the maximum reliability of the path network needs to be determined, the step can also continue to judge whether any 2 directed edges are cut off and the whole directed multi-graph after edge cutting is strongly communicated.
It should be noted that fig. 4 is an example of showing whether any 1 directional edge is cut off and the directional multi-graph after the whole cut edge is strongly connected, and a similar manner to the above may be adopted for the case of judging whether any 2 or more directional edges are cut off and the directional multi-graph after the whole cut edge is strongly connected, which is not limited in this embodiment.
In the embodiment of the invention, the multiple nested annular path networks are converted into the directed multiple graphs, the reliability of the path networks can be calculated by utilizing the connectivity calculation algorithm of the directed multiple graphs, a user can conveniently and quickly judge whether the reliability index of the AGV path networks meets the requirement in practice, and the efficiency of design planning is improved.
Referring to fig. 5, fig. 5 is a block diagram of a reliability calculation apparatus of an AGV path network according to an embodiment of the present invention. The apparatus may include:
a first obtaining module 100, configured to obtain a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle;
a second obtaining module 200, configured to obtain a directed multiple graph corresponding to the path network; the nodes in the directed multi-graph are track intersection points, reverse track turning points and equidirectional track lane change points, and directed edges among the nodes are tracks;
the determining module 300 is configured to determine the reliability of the path network according to a strong connectivity condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1.
Alternatively, when n is equal to 1, the determining module 300 may include:
the first determining submodule is used for judging whether any 1 directed edge is cut off and whether the directed multi-graph after the whole edge is cut off is strongly communicated; if yes, determining the reliability of the path network to be 1; if not, determining the reliability of the path network to be 0.
Alternatively, when n is 2, the determining module 300 may include:
the second determining submodule is used for judging whether any 1 directed edge is cut off and whether the directed multi-graph after the whole edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 0; if yes, sending a starting signal to a third determining submodule;
the third determining submodule is used for judging whether any 2 directed edges are cut off and whether the directed multi-graph after the whole edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 1; and if so, determining the reliability of the path network to be 2.
Optionally, the second determining sub-module may include:
the numbering unit is used for numbering all directed edges in the directed multi-graph and taking the minimum number as the current number;
the calculation unit is used for cutting the directed edge corresponding to the current number in the directed multi-graph and calculating the strongly-connected component of the directed multi-graph after edge cutting by using a preset algorithm;
the first judgment unit is used for judging whether the directed multi-graph after the whole edge is cut is strongly connected or not according to the strongly connected component; if not, determining the reliability of the path network to be 0; if yes, sending a starting signal to a second judgment unit;
a second judging unit, configured to judge whether the current number is the maximum number; if not, taking the next number as the current number, and executing to send a starting signal to the computing unit; and if so, sending a starting signal to a third determining submodule.
Optionally, the second determining sub-module may further include:
and the output unit is used for outputting the directed edge corresponding to the current number and two nodes connected with the directed edge corresponding to the current number if the directed multi-graph after the whole edge cutting is not strongly communicated.
Optionally, the apparatus may further include:
the judging module is used for judging whether the number of the corresponding tracks of each discharge port and each feed port in the path network is more than or equal to 2; if yes, sending a starting signal to a second acquisition module; if not, sending a starting signal to the output module;
and the output module is used for outputting the corresponding tracks of the discharge port and the feed port, the number of which is less than 2, and the connected track intersection point, the reverse track turning point or the equidirectional track changing point.
In this embodiment, the second obtaining module 200 converts the multiple nested ring-shaped path network into the directed multiple graph, and the reliability of the path network can be calculated by using a connectivity calculation algorithm of the directed multiple graph, so that a user can conveniently and quickly judge whether the reliability index of the AGV path network actually meets the requirement, and the efficiency of design planning is improved.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The method and the device for calculating the reliability of the AGV path network provided by the invention are described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the method and its core concepts. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.
Claims (6)
1. A reliability calculation method for an AGV path network is characterized by comprising the following steps:
acquiring a path network of an automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle;
acquiring a directed multi-graph corresponding to the path network; wherein, the nodes in the directed multi-graph are the track intersection point, the reverse track turning point and the equidirectional track changing point, and the directed edges among the nodes are the tracks;
determining the reliability of the path network according to the strong communication condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1;
when n is equal to 1, determining the reliability of the path network according to the strong connectivity condition of the whole edge-truncated directed multi-graph after any n directed edges are truncated, including:
judging whether any 1 directed edge is cut off and whether the directed multiple graphs after the whole cut edge are strongly communicated;
if yes, determining the reliability of the path network to be 1;
if not, determining the reliability of the path network to be 0;
when n is 2, determining the reliability of the path network according to the strong connectivity condition of the whole edge-truncated directed multi-graph after any n directed edges are truncated, including:
judging whether any 1 directed edge is cut off and whether the directed multiple graphs after the whole cut edge are strongly communicated;
if not, determining the reliability of the path network to be 0;
if yes, judging whether any 2 directed edges are cut off and whether the directed multiple graphs after the edges are cut off are strongly communicated;
if not, determining the reliability of the path network to be 1;
and if so, determining the reliability of the path network to be 2.
2. The method of claim 1, wherein said determining whether any 1 of said directed edges are cut off and the entire directed multi-graph is strongly connected comprises:
numbering all the directed edges in the directed multi-graph, and taking the minimum number as the current number;
cutting a directed edge corresponding to the current number from the directed multi-graph, and calculating a strongly-connected component of the cut directed multi-graph by using a preset algorithm;
judging whether the directed multi-graph after the whole edge cutting is strongly connected or not according to the strongly connected component;
if not, executing the step of determining that the reliability of the path network is 0;
if so, judging whether the current number is the maximum number or not;
if the current number is not the maximum number, taking the next number as the current number, executing the step of cutting a directed edge corresponding to the current number in the directed multi-graph, and calculating a strongly-connected component of the directed multi-graph after edge cutting by using a preset algorithm;
and if the current number is the maximum number, executing the step of judging whether any 2 directed edges are cut off and the directed multi-graph after the whole edge is cut off is strongly communicated.
3. The method of calculating reliability for an AGV path network of claim 2 further comprising:
and if the directed multi-graph after the whole edge cutting is not strongly communicated, outputting the directed edge corresponding to the current number and two nodes connected with the directed edge corresponding to the current number.
4. The method for calculating the reliability of an AGV path network according to any one of claims 1 to 3, wherein said obtaining the path network of the automated guided vehicle comprises:
judging whether the number of the corresponding tracks of each discharge port and each feed port in the path network is more than or equal to 2;
if yes, executing the step of obtaining the directed multiple graph corresponding to the path network;
if not, outputting the corresponding tracks of which the number is less than 2 of the discharge port and the feed port, and connecting the track intersection point, the reverse track turning point or the equidirectional track changing point.
5. A reliability calculation device for an AGV path network, comprising:
the first acquisition module is used for acquiring a path network of the automatic guided vehicle; the path network comprises a track junction point, a reverse track turning point, a same-direction track changing point and a track comprising the running direction of the automatic guided vehicle;
the second acquisition module is used for acquiring the directed multiple graph corresponding to the path network; wherein, the nodes in the directed multi-graph are the track intersection point, the reverse track turning point and the equidirectional track changing point, and the directed edges among the nodes are the tracks;
the determining module is used for determining the reliability of the path network according to the strong connection condition of the whole directed multi-graph after cutting any n directed edges; wherein n is a positive integer greater than or equal to 1;
wherein when n is 1, the determining module includes:
the first determining submodule is used for judging whether any 1 directed edge is cut off and whether the directed multi-graph after the whole edge is cut off is strongly communicated; if yes, determining the reliability of the path network to be 1; if not, determining the reliability of the path network to be 0;
when n is 2, the determining module includes:
the second determining submodule is used for judging whether any 1 directed edge is cut off and whether the whole directed multi-graph after the edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 0; if yes, sending a starting signal to a third determining submodule;
the third determining submodule is used for judging whether any 2 directed edges are cut off and the directed multi-graph after the whole edge is cut off is strongly communicated; if not, determining the reliability of the path network to be 1; and if so, determining the reliability of the path network to be 2.
6. The AGV path network reliability calculation apparatus of claim 5 further comprising:
the judging module is used for judging whether the number of the corresponding tracks of each discharge port and each feed port in the path network is more than or equal to 2; if yes, sending a starting signal to the second acquisition module; if not, sending a starting signal to the output module;
the output module is used for outputting the corresponding tracks of the discharge port and the feed port, the number of the corresponding tracks of which is less than 2, and the track junction, the reverse track turning point or the equidirectional track changing point which are connected with the corresponding tracks.
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| CN112288270B (en) * | 2020-10-28 | 2023-09-29 | 湖南大学 | Scheduling method for complex rail transmission system |
| CN115063088B (en) * | 2022-08-16 | 2022-11-08 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things system for material transportation control and control method |
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