CN117289669A

CN117289669A - Automatic adjustment type production line control system and method based on industrial large model

Info

Publication number: CN117289669A
Application number: CN202311585386.2A
Authority: CN
Inventors: 张发恩; 徐辉; 张梦媛; 肖磊
Original assignee: Qingdao Chuangxin Qizhi Technology Group Co ltd
Current assignee: Innovation Qizhi Technology Group Co ltd
Priority date: 2023-11-27
Filing date: 2023-11-27
Publication date: 2023-12-26
Anticipated expiration: 2043-11-27
Also published as: CN117289669B

Abstract

The application provides an automatic adjustment type production line control system and method based on an industrial large model, which relate to the field of artificial intelligence and are used for ensuring the stability of network services of an intelligent production line. The method comprises the following steps: the management equipment acquires the communication service quality of the area where the park production line is located at the first time from an operator network; the management equipment processes the communication service quality of the area of the park production line at a first time through the industrial large model so as to estimate the communication service quality of the area of the park production line at a second time, wherein the second time is after the first time; the management device requests the operator network to provide the signal enhancement service for the target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

Description

Automatic adjustment type production line control system and method based on industrial large model

Technical Field

The application relates to the field of artificial intelligence, in particular to an automatic adjustment type production line control system and method based on an industrial large model.

Background

The intelligent production line is a highly-automatic production mode, and the intellectualization, automation and visualization of the production process are realized by introducing advanced sensor, robot and artificial intelligence technologies. The intelligent production line can greatly improve the production efficiency, reduce the production cost, improve the product quality and reduce the dependence on labor force.

The 5G network covered by the whole park can provide stable and efficient communication support for the intelligent production line, so that each link of the production line can realize real-time monitoring and data transmission, and the cooperative efficiency of the production line is improved. In addition, the 5G network covered by the whole production park can provide services such as remote monitoring and remote control for enterprises, realize real-time monitoring and management of the whole production park, and improve the management level and production efficiency of the enterprises.

However, due to instability of wireless communication, random attenuation occurs in channel quality of the 5G network, which affects stability of network service of the intelligent production line, so how to guarantee stability of network service of the intelligent production line is a hot problem of current research.

Disclosure of Invention

The embodiment of the application provides an automatic adjustment type production line control system and method based on an industrial large model, which are used for guaranteeing the stability of network service of an intelligent production line.

In order to achieve the above purpose, the present application adopts the following technical scheme:

in a first aspect, embodiments of the present application provide an automatic adjustment type production line control method based on an industrial large model, where the method is applied to a management device of a campus production line, and the method includes: the management equipment acquires the communication service quality of the area where the park production line is located at the first time from an operator network; the management equipment processes the communication service quality of the area of the park production line at a first time through the industrial large model so as to estimate the communication service quality of the area of the park production line at a second time, wherein the second time is after the first time; the management device requests the operator network to provide the signal enhancement service for the target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

Optionally, the management device obtains, from the operator network, communication service quality of the area where the campus production line is located at the first time, including: the management equipment requests the communication service quality of the area where the operator network open park production line is located; the management device receives the communication service quality of the area where the open park production line is located at the first time according to the request of the management device by the operator network.

Optionally, the management device requests a communication service quality of an area where the operator network open park production line is located, including: the management equipment sends a network capability opening request to NEF network elements of an operator network, wherein the capability opening request carries information for indicating the area of a park production line and information for requesting the open communication service quality, the information for indicating the area of the park production line is converted into a corresponding cell identification list by the NEF network elements, and at least one cell indicated by the cell identification list covers the area of the park production line; the management device receives communication service quality of an area where an open park production line is located at a first time according to a request of the management device from an operator network, and the communication service quality comprises: the management device receives a capability opening response returned by the operator network according to the capability opening request, wherein the capability opening response comprises a first communication service quality in each of M x N grids and information for indicating first time, and an area where the park production line is located is divided into M x N grids, and M and N are integers larger than 1.

That is, the NEF network element may find RAN devices corresponding to the cells according to the cell identification list, and then send information indicating an area where the campus line is located to the RAN devices, so as to request the RAN devices to measure the communication service quality of the area. The RAN device may divide the area into m×n grids according to the information indicating the area where the campus line is located (specific division logic or policy may be determined based on a policy local to the RAN device, which is not limited to this), and allocate a corresponding identifier to each grid, so that the identifier can be identified in the subsequent reporting. The RAN device may then measure a first quality of service, such as RSRP, for the communication within each grid at a first time (e.g., current). Wherein, the measurement may be that the RAN device gives way to one or more UEs located in each grid to report the RSRP measured by itself, and the average value of the weighted sum of the one or more RSRP may be used as the first communication service quality in the grid.

It will be appreciated that there may be a plurality of RAN devices whose cells cover the area. In this case, a RAN device (i.e., a target RAN device) may divide the grids, and then the target RAN device distributes the divided m×n grids to the remaining RAN devices, where each RAN device measures only the first communication service quality in the grids that can be covered by its own cell at the first time, and reports the first communication service quality to the target RAN device, and the target RAN device gathers the first communication service quality in each of the m×n grids. The target RAN device may be specified by the NEF network element, or predefined by a protocol, which is not limited.

Optionally, the managing device processes, through the industrial large model, the communication service quality of the area of the campus line at the first time to predict the communication service quality of the area of the campus line at the second time, including: the management device inputs the first communication service quality in each of the M x N grids into the industrial large model to obtain the second communication service quality in each of the M x N grids after a preset time length, wherein the preset time length after the first time is the second time, and the second communication service quality is output by the industrial large model.

Optionally, the management device inputs the first communication service quality in each of the m×n grids to the industrial large model to obtain the second communication service quality in each of the m×n grids after the preset duration, where the second communication service quality is output by the industrial large model, where the convolution neural network model of the industrial large model includes: the management device maps the first communication service quality in each of the m×n grids into a first grid image, wherein the first grid image comprises m×n grids, each of the m×n grids in the first grid image corresponds to one of the m×n grids, and a gray value filled in each of the m×n grids in the first grid image represents the first communication service quality of one of the grids corresponding to the grid; the management device inputs the first grid image into the convolutional neural network model to obtain a second grid image output by the convolutional neural network model, wherein the second grid image comprises M x N grids, each grid of the M x N grids in the second grid image corresponds to one grid of the M x N grids, and the filled gray value of each grid of the M x N grids in the second grid image represents the second communication service quality of one grid corresponding to the grid; the management device inversely maps the second mesh image to a second quality of communication service within each of the M x N grids.

Optionally, the input data format of the recurrent neural network model of the industrial large model is output L data, where L is greater than or equal to m×n, and the management device inputs the first communication service quality in each of the m×n grids to the industrial large model to obtain the second communication service quality in each of the m×n grids after the preset duration, where the second communication service quality in each of the m×n grids is output by the industrial large model, where the method includes: the management device takes the first communication service quality in each of M x N grids as first data, wherein the first M x N first data are the same, and the management device fills the last L-M x N first data into 0; the management device inputs the first data of the first M times N items and the first data of the last L-M times N items into the recurrent neural network model to obtain the second data of the L items output by the recurrent neural network model, wherein the second data of the first M times N items in the second data of the L items are the second communication service quality in each grid in M times N grids, and the second data of the last L-M times N items in the second data of the L items are 0.

Optionally, the management device requests the operator network to provide the signal enhancement service for the target area in the area of the campus production line according to the scheduling situation of the campus production line and the communication service quality of the area of the campus production line at the second time, including: the management device determines at least one grid to be selected, wherein the second communication service quality of the grids is smaller than a communication service quality threshold value; the method comprises the steps of managing the production situation of a production line of an equipment park, determining at least one target grid from at least one grid to be selected, wherein the production line in the area where the at least one target grid is located has a yield greater than a yield threshold, and the area formed by the at least one target grid is a target area; the management device requests the operator network to provide signal enhancement services for the target area.

Optionally, the management device requests the operator network to provide the signal enhancement service for the target area, including: the management device sends an enhanced service request to a NEF network element in the operator network, wherein the enhanced service request includes an identification of each of the at least one target grid, a second quality of service of each of the at least one target grid, information indicating a second time, and a cell for requesting a signal enhanced service.

Alternatively, the signal enhancement service refers to that the beam of the RAN device reflected by the RIS irradiates an area where the signal enhancement service needs to be obtained together with the beam emitted by the RAN device itself.

For example, the NEF network element may send the respective identity of the at least one target grid, the respective second communication quality of service of the at least one target grid, the information indicating the second time, and the information element for requesting the signal enhancement service to the RAN device, such as the target RAN device, that performed the measurement in advance. The target RAN device may determine, according to the respective identifier of the at least one target grid, the respective second communication service quality of the at least one target grid, information indicating the second time, and then at the second time, a channel of the at least one target grid may fade, which results in poor communication service quality. Thus, at the target RAN device, the scheduling beam can cover the RIS of at least one target grid, e.g., control the reflection direction of the RIS, based on the cells used to request the signal enhancement services. For example, the target RAN device transmits indication information to a RAN device serving the at least one target grid to indicate that it is to transmit a beam to the RIS at a second time while transmitting a beam to the at least one target grid, while the target RAN device is further configured to direct the reflection direction of the RIS toward the at least one target grid, and the validation time is the second time. In this way, at the second time, the beam of the RAN device serving the at least one target grid can be directly irradiated not only to the at least one target grid, but also reflected by the RIS to the at least one target grid, thereby achieving the signal enhancement service.

In a second aspect, embodiments of the present application provide an industrial large model-based self-tuning line control system including a management device for a campus line, the system configured to: the management equipment acquires the communication service quality of the area where the park production line is located at the first time from an operator network; the management equipment processes the communication service quality of the area of the park production line at a first time through the industrial large model so as to estimate the communication service quality of the area of the park production line at a second time, wherein the second time is after the first time; the management device requests the operator network to provide the signal enhancement service for the target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

Optionally, the system is configured to: the management equipment requests the communication service quality of the area where the operator network open park production line is located; the management device receives the communication service quality of the area where the open park production line is located at the first time according to the request of the management device by the operator network.

Optionally, the system is configured to: the management equipment sends a network capability opening request to NEF network elements of an operator network, wherein the capability opening request carries information for indicating the area of a park production line and information for requesting the open communication service quality, the information for indicating the area of the park production line is converted into a corresponding cell identification list by the NEF network elements, and at least one cell indicated by the cell identification list covers the area of the park production line; the management device receives communication service quality of an area where an open park production line is located at a first time according to a request of the management device from an operator network, and the communication service quality comprises: the management device receives a capability opening response returned by the operator network according to the capability opening request, wherein the capability opening response comprises a first communication service quality in each of M x N grids and information for indicating first time, and an area where the park production line is located is divided into M x N grids, and M and N are integers larger than 1.

Optionally, the system is configured to: the management device inputs the first communication service quality in each of the M x N grids into the industrial large model to obtain the second communication service quality in each of the M x N grids after a preset time length, wherein the preset time length after the first time is the second time, and the second communication service quality is output by the industrial large model.

Optionally, the convolutional neural network model of the industrial large model, the system is configured to: the management device maps the first communication service quality in each of the m×n grids into a first grid image, wherein the first grid image comprises m×n grids, each of the m×n grids in the first grid image corresponds to one of the m×n grids, and a gray value filled in each of the m×n grids in the first grid image represents the first communication service quality of one of the grids corresponding to the grid; the management device inputs the first grid image into the convolutional neural network model to obtain a second grid image output by the convolutional neural network model, wherein the second grid image comprises M x N grids, each grid of the M x N grids in the second grid image corresponds to one grid of the M x N grids, and the filled gray value of each grid of the M x N grids in the second grid image represents the second communication service quality of one grid corresponding to the grid; the management device inversely maps the second mesh image to a second quality of communication service within each of the M x N grids.

Optionally, the recurrent neural network model of the industrial large model, the system is configured to: the management device takes the first communication service quality in each of M x N grids as first data, wherein the first M x N first data are the same, and the management device fills the last L-M x N first data into 0; the management device inputs the first data of the first M times N items and the first data of the last L-M times N items into the recurrent neural network model to obtain the second data of the L items output by the recurrent neural network model, wherein the second data of the first M times N items in the second data of the L items are the second communication service quality in each grid in M times N grids, and the second data of the last L-M times N items in the second data of the L items are 0.

Optionally, the system is configured to: the management device determines at least one grid to be selected, wherein the second communication service quality of the grids is smaller than a communication service quality threshold value; the method comprises the steps of managing the production situation of a production line of an equipment park, determining at least one target grid from at least one grid to be selected, wherein the production line in the area where the at least one target grid is located has a yield greater than a yield threshold, and the area formed by the at least one target grid is a target area; the management device requests the operator network to provide signal enhancement services for the target area.

Optionally, the system is configured to: the management device sends an enhanced service request to a NEF network element in the operator network, wherein the enhanced service request includes an identification of each of the at least one target grid, a second quality of service of each of the at least one target grid, information indicating a second time, and a cell for requesting a signal enhanced service.

In a third aspect, embodiments of the present application provide a computer readable storage medium having program code stored thereon, which when executed by the computer, performs the method according to the first aspect.

In summary, the method and the device have the following technical effects:

the management device can estimate the communication service quality of the area where the park production line is located at the first time through the industrial large model based on the communication service quality of the area where the park production line is located at the first time, so as to determine which areas (such as target areas) may be attenuated in the future, thereby requesting the operator network to provide signal enhancement services for the target areas, avoiding the influence caused by signal attenuation, and ensuring the stability of network services of the intelligent production line.

Drawings

FIG. 1 is a schematic diagram of a 5G system architecture;

FIG. 2 is a schematic diagram of a production system according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of an automatic adjustment type production line control method based on an industrial large model according to an embodiment of the present application;

fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

1. Fifth generation (5th generation,5G) mobile communication system:

fig. 1 is a schematic architecture diagram of a 5G system, as shown in fig. 1, where the 5G system includes: access Networks (ANs) and Core Networks (CNs), may further include: and (5) a terminal.

The terminal may be a terminal having a transceiver function, or a chip system that may be provided in the terminal. The terminal may also be referred to as a User Equipment (UE), an access terminal, a subscriber unit (subscriber unit), a subscriber station, a Mobile Station (MS), a remote station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent, or a user device. The terminals in embodiments of the present application may be mobile phones (mobile phones), cellular phones (cellular phones), smart phones (smart phones), tablet computers (pads), wireless data cards, personal digital assistants (personal digital assistant, PDAs), wireless modems (modems), handheld devices (handsets), laptop computers (lap computers), machine type communication (machine type communication, MTC) terminals, computers with wireless transceiving functions, virtual Reality (VR) terminals, augmented reality (augmented reality, AR) terminals, wireless terminals in industrial control (industrial control), wireless terminals in unmanned aerial vehicle (self driving), wireless terminals in smart grid (smart grid), wireless terminals in transportation security (transportation safety), wireless terminals in smart city (smart city), wireless terminals in smart home (smart home), roadside units with functions, RSU, etc. The terminal of the present application may also be an in-vehicle module, an in-vehicle component, an in-vehicle chip, or an in-vehicle unit built into a vehicle as one or more components or units.

The AN is used for realizing the function related to access, providing the network access function for authorized users in a specific area, and determining transmission links with different qualities according to the level of the users, the service requirements and the like so as to transmit user data. The AN forwards control signals and user data between the terminal and the CN. The AN may include: an access network element, which may also be referred to as a radio access network element (radio access network, RAN) device.

The RAN device may be a device that provides access to the terminal. For example, the RAN device may include: the RAN apparatus may also include a 5G, such as a gNB in a new radio, NR, system, or one or a group (including multiple antenna panels) of base stations in the 5G, or may also be a network node, such as a baseband unit (building base band unit, BBU), or a Centralized Unit (CU) or a Distributed Unit (DU), an RSU with base station functionality, or a wired access gateway, or a core network element of the 5G, constituting a gNB, a transmission point (transmission and reception point, TRP or transmission point, TP), or a transmission measurement function (transmission measurement function, TMF). Alternatively, the RAN device may also include an Access Point (AP) in a wireless fidelity (wireless fidelity, wiFi) system, a wireless relay node, a wireless backhaul node, various forms of macro base stations, micro base stations (also referred to as small stations), relay stations, access points, wearable devices, vehicle devices, and so on. Alternatively, the RAN device may also include a next generation mobile communication system, for example, an access network element of 6G, for example, a 6G base station, or in the next generation mobile communication system, the network device may also have other naming manners, which are covered in the protection scope of the embodiments of the present application, which is not limited in any way.

The CN is mainly responsible for maintaining subscription data of the mobile network and providing session management, mobility management, policy management, security authentication and other functions for the terminal. The CN mainly comprises the following network elements: a user plane function (user plane function, UPF) network element, an authentication service function (authentication server function, AUSF) network element, an access and mobility management function (access and mobility management function, AMF) network element, a session management function (session management function, SMF) network element, a network slice selection function (network slice selection function, NSSF) network element, a network opening function (network exposure function, NEF) network element, a network function warehousing function (NF repository function, NRF) network element, a policy control function (policy control function, PCF) network element, a unified data management (unified data management, UDM) network element, an application function (application function, AF) network element, and a network slice and independent non-public network (nsaaf) authentication authorization function (network slice-specific and SNPN authentication and authorization function, nsaaf) network element.

Wherein the UPF network element is mainly responsible for user data processing (forwarding, receiving, charging, etc.). For example, the UPF network element may receive user data from a Data Network (DN), which is forwarded to the terminal through the access network element. The UPF network element may also receive user data from the terminal through the access network element and forward the user data to the DN. DN network elements refer to the operator network that provides data transmission services for subscribers. Such as the internet protocol (internet protocol, IP) Multimedia Services (IMS), the internet, etc.

The AUSF network element may be used to perform security authentication of the terminal.

The AMF network element is mainly responsible for mobility management in the mobile network. Such as user location updates, user registration networks, user handoffs, etc.

The SMF network element is mainly responsible for session management in the mobile network. Such as session establishment, modification, release. Specific functions are, for example, assigning internet protocol (internet protocol, IP) addresses to users, selecting a UPF that provides a message forwarding function, etc.

The PCF network element mainly supports providing a unified policy framework to control network behavior, provides policy rules for a control layer network function, and is responsible for acquiring user subscription information related to policy decision. The PCF network element may provide policies, such as quality of service (quality of service, qoS) policies, slice selection policies, etc., to the AMF network element, SMF network element.

The NSSF network element may be used to select a network slice for the terminal.

The NEF network element may be used to support the opening of capabilities and events.

The UDM network element may be used to store subscriber data, such as subscription data, authentication/authorization data, etc.

The AF network element mainly supports interactions with the CN to provide services, such as influencing data routing decisions, policy control functions or providing some services of a third party to the network side.

2. Beam:

the beam may be embodied in a protocol that may be spatial filter (spatial domain filter), or spatial filter, or spatial parameter (spatial domain parameter), spatial parameter (spatial parameter), spatial setting (spatial domain setting), spatial setting (spatial setting), or Quasi co-location (QCL) information, QCL hypothesis, QCL indication, etc. The beam may be indicated by a transmission configuration indication state (Transmission Configuration Indication state) parameter or by a spatial relationship (spatial relationship) parameter. Thus, in this application, beams may be replaced by spatial filters, spatial parameters, spatial settings, QCL information, QCL hypotheses, QCL indications, TCI states (DL TCI-states), spatial relationships, etc. The terms are also equivalent to each other. The beam may also be replaced with other terms that denote a beam, and the present application is not limited thereto.

The beams used to transmit signals may be referred to as transmit beams (transmission beam, tx beams), such as uplink transmit beams or downlink transmit beams, may also be referred to as spatial transmit filters (spatial domain transmission filter), spatial transmit filters (spatial transmission filter), spatial transmit parameters (spatial domain transmission parameter) or spatial transmit parameters (spatial transmission parameter), spatial transmit settings (spatial domain transmission setting) or spatial transmit settings (spatial transmission setting). The downlink transmit beam may be indicated by a TCI status.

The beams used to receive the signal may be referred to as receive beams (Rx beams), such as uplink receive beams or downlink receive beams, may also be referred to as spatial receive filters (spatial domain reception filter), spatial receive filters (spatial reception filter), spatial receive parameters (spatial domain reception parameter) or spatial receive parameters (spatial reception parameter), spatial receive settings (spatial domain reception setting) or spatial receive settings (spatial reception setting). The transmit beams may be indicated by spatial relationships, or uplink TCI states, or sounding reference signal (Sounding Reference Signal, SRS) resources (representing the transmit beam in which the SRS is employed). The uplink transmit beam may also be replaced with SRS resources.

The transmit beam may also refer to the distribution of signal intensities formed in spatially different directions after a signal is transmitted through an antenna, and the receive beam may also refer to the distribution of signal intensities in spatially different directions for a wireless signal received from the antenna.

Furthermore, the beam may be a wide beam, or a narrow beam, or other type of beam. The technique of forming the beam may be a beamforming technique or other technique. The beamforming technique may specifically be a digital beamforming technique, an analog beamforming technique, or a hybrid digital/analog beamforming technique, etc.

The beam generally corresponds to a resource, for example, when the network device measures the beam, the network device measures different beams through different resources, the terminal feeds back the measured quality of the resource, and the network device knows the quality of the corresponding beam. At the time of data transmission, beam information is also indicated by its corresponding resource. The network device indicates information of a physical downlink shared channel (physical downlink sharing channel, PDSCH) beam of the terminal, for example, through a transmission configuration number (transmission configuration indication, TCI) field in downlink control information (downlink control information, DCI).

Alternatively, a plurality of beams having the same or similar communication characteristics are regarded as one beam. One or more antenna ports may be included in a beam for transmitting data channels, control channels, and sounding signals, etc. One or more antenna ports forming a beam may also be considered as a set of antenna ports. In beam measurement, each beam corresponds to a resource, and thus the beam to which the resource corresponds can be uniquely identified by an index of the resource.

3. Deep neural network (deep neural network, DNN):

DNN is a specific implementation of machine learning. According to the general approximation theorem, the neural network can theoretically approximate any continuous function, so that the neural network has the capability of learning any mapping. DNNs can be classified into feed-forward neural networks (feed forward neural network, FNN), convolutional neural networks (convolutional neural networks, CNN) and recurrent neural networks (recurrent neural network, RNN) according to the manner in which the network is constructed.

The characteristic of the FNN network is that the neurons of adjacent layers are completely connected in pairs, which makes FNNs usually require a large amount of memory space and results in high computational complexity.

CNN is a neural network dedicated to processing data having a grid-like structure. For example, both time-series data (time-axis discrete sampling) and image data (two-dimensional discrete sampling) can be regarded as data resembling a grid structure. The CNN does not use all input information for operation at one time, but uses window interception part information with a fixed size for convolution operation, thereby greatly reducing the calculation amount of model parameters. In addition, according to the different types of information intercepted by the windows (such as different types of information of people and objects in the same figure), each window can adopt different convolution kernel operations, so that the CNN can better extract the characteristics of input data.

RNNs are a class of DNN networks that utilize feedback time series information. Its inputs include the new input value at the current time and its own output value at the previous time. The RNN is suitable for obtaining sequence features having a correlation in time, and is particularly suitable for applications such as speech recognition, channel coding and the like.

In the embodiment of the invention, the indication can comprise direct indication and indirect indication, and can also comprise explicit indication and implicit indication. In the specific implementation process, the manner of indicating the information to be indicated is various, for example, but not limited to, the information to be indicated may be directly indicated, such as the information to be indicated itself or an index of the information to be indicated. The information to be indicated can also be indicated indirectly by indicating other information, wherein the other information and the information to be indicated have an association relation. It is also possible to indicate only a part of the information to be indicated, while other parts of the information to be indicated are known or agreed in advance. For example, the indication of the specific information may also be achieved by means of a pre-agreed (e.g., protocol-specified) arrangement sequence of the respective information, thereby reducing the indication overhead to some extent. And meanwhile, the universal part of each information can be identified and indicated uniformly, so that the indication cost caused by independently indicating the same information is reduced.

The specific indication means may be any of various existing indication means, such as, but not limited to, the above indication means, various combinations thereof, and the like. Specific details of various indications may be referred to the prior art and are not described herein. As can be seen from the above, for example, when multiple pieces of information of the same type need to be indicated, different manners of indication of different pieces of information may occur. In a specific implementation process, a required indication mode can be selected according to specific needs, and the selected indication mode is not limited in the embodiment of the present invention, so that the indication mode according to the embodiment of the present invention is understood to cover various methods that can enable a party to be indicated to learn information to be indicated.

It should be understood that the information to be indicated may be sent together as a whole or may be sent separately in a plurality of sub-information, and the sending periods and/or sending timings of these sub-information may be the same or different. Specific transmission method the embodiment of the present invention is not limited. The transmission period and/or the transmission timing of the sub-information may be predefined, for example, predefined according to a protocol, or may be configured by the transmitting end device by transmitting configuration information to the receiving end device.

The "pre-defining" or "pre-configuring" may be implemented by pre-storing corresponding codes, tables, or other manners that may be used to indicate relevant information in the device, and the embodiments of the present invention are not limited to the specific implementation manner. Where "save" may refer to saving in one or more memories. The one or more memories may be provided separately or may be integrated in an encoder or decoder, processor, or electronic device. The one or more memories may also be provided separately as part of a decoder, processor, or electronic device. The type of memory may be any form of storage medium, and embodiments of the invention are not limited in this regard.

The "protocol" referred to in the embodiments of the present invention may refer to a protocol family in the communication field, a standard protocol similar to a frame structure of the protocol family, or a related protocol applied to a reliable access method system of future internet of things equipment, which is not specifically limited in the embodiments of the present invention.

In the embodiment of the invention, the descriptions of "when … …", "in the case of … …", "if" and "if" all refer to that the device will perform corresponding processing under some objective condition, and are not limited in time, nor do the descriptions require that the device must have a judging action when implementing, nor do the descriptions mean that other limitations exist.

In the description of the embodiments of the present invention, unless otherwise indicated, "/" means that the objects associated in tandem are in a "or" relationship, e.g., A/B may represent A or B; the "and/or" in the embodiment of the present invention is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a alone, a and B together, and B alone, wherein A, B may be singular or plural. Also, in the description of the embodiments of the present invention, unless otherwise indicated, "plurality" means two or more than two. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present invention, in the embodiments of the present invention, the words "first", "second", etc. are used to distinguish the same item or similar items having substantially the same function and effect. It will be appreciated by those of skill in the art that the words "first," "second," and the like do not limit the amount and order of execution, and that the words "first," "second," and the like do not necessarily differ. Meanwhile, in the embodiments of the present invention, words such as "exemplary" or "such as" are used to mean serving as examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g." in an embodiment should not be taken as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion that may be readily understood.

The network architecture and the service scenario described in the embodiments of the present invention are for more clearly describing the technical solution of the embodiments of the present invention, and do not constitute a limitation on the technical solution provided by the embodiments of the present invention, and those skilled in the art can know that, with the evolution of the network architecture and the appearance of the new service scenario, the technical solution provided by the embodiments of the present invention is applicable to similar technical problems.

The technical solutions in the present application will be described below with reference to the accompanying drawings.

Referring to fig. 2, an embodiment of the present application provides a production system, which may include: management devices and operator networks.

The management device may be understood as a terminal, which may be a terminal having a communication function, or may be a chip or a chip system provided in the terminal. The terminal device may also be referred to as a User Equipment (UE), an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent, or a user device. The terminal device in the embodiment of the present application may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an augmented reality (augmented reality, AR) terminal device, a wireless terminal in industrial control (industrial control), a wireless terminal in unmanned driving (self driving), a wireless terminal in remote medical (remote medical), a wireless terminal in smart grid (smart grid), a wireless terminal in transportation security (transportation safety), a wireless terminal in smart city (smart city), a wireless terminal in smart home (smart home), a vehicle-mounted terminal, an RSU with a terminal function, or the like.

The interaction of the management device and the operator network in the above-described production system will be described in detail below in connection with the method.

Referring to fig. 3, an embodiment of the present application provides a method for controlling an automatically adjusted production line based on an industrial large model. The method may be applicable to communication between a management device and a control device. The method comprises the following steps:

s301, the management equipment acquires the communication service quality of the area where the park production line is located at the first time from the operator network.

The management device may request communication service quality of an area where the operator network open park production line is located. For example, the management device sends a network capability opening request to a NEF network element of the operator network, where the capability opening request carries information for indicating an area where a campus production line is located, and a cell for requesting an open communication service quality, where the information for indicating the area where the campus production line is located is converted into a corresponding cell identification list by the NEF network element, and at least one cell indicated by the cell identification list covers the area where the campus production line is located.

The management device may receive a communication service quality of the first time of the area where the open campus line is located by the operator network according to the request of the management device. For example, the management device may receive a capability openness response returned by the operator network according to the capability openness request. The capacity open response includes a first communication service quality in each of m×n grids, and information indicating a first time, and an area where the campus line is located is divided into m×n grids, where M and N are integers greater than 1.

S302, the management equipment processes the communication service quality of the area of the park production line at the first time through the industrial large model so as to estimate the communication service quality of the area of the park production line at the second time.

Wherein the second time is after the first time. The management device may input the first communication service quality in each of the m×n grids to the industrial large model, to obtain a second communication service quality in each of the m×n grids after a preset duration output by the industrial large model, where the preset duration after the first time is the second time.

Mode 1, convolutional neural network model of industrial large model.

The management device may map the first communication service quality within each of the m×n grids to a first grid image, where the first grid image includes m×n grids, each of the m×n grids in the first grid image corresponds to one of the m×n grids, and a gray value filled in each of the m×n grids in the first grid image indicates the first communication service quality of the one grid corresponding to the one grid. The management device may input the first grid image to the convolutional neural network model, and obtain a second grid image output by the convolutional neural network model, where the second grid image includes m×n grids, each of the m×n grids in the second grid image corresponds to one of the m×n grids, and a gray value filled in each of the m×n grids in the second grid image indicates a second communication service quality of one of the grids corresponding to the grid. The management device may inverse map the second mesh image to a second quality of communication service within each of the M x N grids.

In mode 2, the input data format of the recurrent neural network model is output L data, and L is greater than or equal to m×n.

The management device may use the first communication service quality in each of the m×n grids as one first data, and the management device fills the last L-m×n first data with 0. The management device may input the first data of the first m×n items and the first data of the second L-m×n items into the recurrent neural network model, so as to obtain the second data of the L items output by the recurrent neural network model. The first m×n second data in the L second data are second communication quality of service in each of the m×n grids, and the last L-m×n second data in the L second data are 0.

And S303, the management equipment requests the operator network to provide signal enhancement service for the target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

The management device may determine at least one candidate grid of the M x N grids for which the second communication quality of service is less than the communication quality of service threshold. The management device can determine at least one target grid from at least one grid to be selected according to the production situation of the production line of the park, the production line in the area where the at least one target grid is located is larger than the production threshold, and the area formed by the at least one target grid is the target area. That is, the selection signal may be degraded, and the productivity of the corresponding production line is relatively large. The management device may request the carrier network to provide signal enhancement services for the target area. For example, the management device may send an enhanced services request to a NEF network element in the operator network. Wherein the enhanced services request comprises an identification of each of the at least one target grid, a second quality of service of each of the at least one target grid, information indicative of a second time, and a cell for requesting signal enhanced services. Alternatively, the signal enhancement service refers to that the beam of the RAN device reflected by the RIS irradiates an area where the signal enhancement service needs to be obtained together with the beam emitted by the RAN device itself.

In summary, the management device may estimate, based on the communication service quality of the area where the campus production line is located at the first time from the operator network, the communication service quality of the area at the second time through the industrial large model to determine which areas (such as the target area) may have attenuation of the signal in the future, so as to request the operator network to provide the signal enhancement service for the target area, so as to avoid the influence caused by the signal attenuation, and ensure the stability of the network service of the intelligent production line.

The method provided in the embodiment of the present application is described in detail above in connection with fig. 3. The following describes an industrial large model-based, self-tuning production line control system for performing the methods provided by embodiments of the present application.

The system includes a management device for a campus line, the system configured to: the management equipment acquires the communication service quality of the area where the park production line is located at the first time from an operator network; the management equipment processes the communication service quality of the area of the park production line at a first time through the industrial large model so as to estimate the communication service quality of the area of the park production line at a second time, wherein the second time is after the first time; the management device requests the operator network to provide the signal enhancement service for the target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

The following describes the various constituent elements of the electronic device 500 in detail with reference to fig. 4:

the processor 501 is a control center of the electronic device 500, and may be one processor or a collective term of a plurality of processing elements. For example, processor 501 is one or more central processing units (central processing unit, CPU), but may also be an integrated circuit (application specific integrated circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present application, such as: one or more microprocessors (digital signal processor, DSPs), or one or more field programmable gate arrays (field programmable gate array, FPGAs).

Alternatively, the processor 501 may perform various functions of the electronic device 500, such as the functions in the method shown in FIG. 3 described above, by running or executing a software program stored in the memory 502 and invoking data stored in the memory 502.

In a particular implementation, the processor 501 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 4, as an embodiment.

In a particular implementation, as one embodiment, the electronic device 500 may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).

The memory 502 is configured to store a software program for executing the present application, and the processor 501 controls the execution of the software program, and the specific implementation may refer to the above method embodiment, which is not described herein again.

Alternatively, memory 502 may be read-only memory (ROM) or other type of static storage device that may store static information and instructions, random access memory (random access memory, RAM) or

Other types of dynamic storage devices, which can store information and instructions, can also be, but are not limited to, an electrically erasable programmable read-only memory (EEPROM), a compact disk read-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disc, etc.), magnetic disk storage or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer. The memory 502 may be integral with the processor 501 or may exist separately from the processor and the electronic device 500

Is coupled to the processor 501 (not shown in fig. 4), as embodiments of the present application are not particularly limited.

A transceiver 503 for communication with other devices. For example, the multi-beam based positioning device is a terminal and the transceiver 503 may be used to communicate with a network device or with another terminal.

Alternatively, the transceiver 503 may include a receiver and a transmitter (not separately shown in fig. 4). The receiver is used for realizing the receiving function, and the transmitter is used for realizing the transmitting function.

Alternatively, the transceiver 503 may be integrated with the processor 501, or may exist separately, and be coupled to the processor 501 through an interface circuit (not shown in fig. 4) of the electronic device 500, which is not specifically limited in this embodiment of the present application.

It should be noted that the structure of the electronic device 500 shown in fig. 4 does not limit the apparatus, and the actual electronic device 500 may include more or less components than those shown, or may combine some components, or may be different in arrangement of components.

In addition, the technical effects of the method according to the above method embodiment may be referred to for the technical effects of the electronic device 500, which are not described herein.

It should be appreciated that the processor in embodiments of the present application may be a central processing unit (central processing unit, CPU), which may also be other general purpose processors, digital signal processors (digital signal processor, DSP), application specific integrated circuits (application specific integrated circuit, ASIC), off-the-shelf programmable gate arrays (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

It should also be appreciated that the memory in embodiments of the present application may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. The volatile memory may be random access memory (random access memory, RAM) which acts as an external cache. By way of example but not limitation, many forms of random access memory (random access memory, RAM) are available, such as Static RAM (SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic Random Access Memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced Synchronous Dynamic Random Access Memory (ESDRAM), synchronous Link DRAM (SLDRAM), and direct memory bus RAM (DR RAM).

The above embodiments may be implemented in whole or in part by software, hardware (e.g., circuitry), firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions in accordance with the embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.) means. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc. that contain one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.

It should be understood that the term "and/or" is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: there are three cases, a alone, a and B together, and B alone, wherein a, B may be singular or plural. In addition, the character "/" herein generally indicates that the associated object is an "or" relationship, but may also indicate an "and/or" relationship, and may be understood by referring to the context.

In the present application, "at least one" means one or more, and "a plurality" means two or more. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b, or c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. 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 application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the partitioning of elements is merely a logical functional partitioning, and there may be additional partitioning in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some feature fields may be omitted, or not implemented. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes or substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An automatic adjustment type production line control method based on an industrial large model, which is applied to management equipment of a park production line and comprises the following steps of:

the management equipment acquires the communication service quality of the area where the park production line is located at the first time from an operator network;

the management equipment processes the communication service quality of the area of the park production line at a first time through an industrial large model so as to estimate the communication service quality of the area of the park production line at a second time, wherein the second time is after the first time;

and the management equipment requests the operator network to provide signal enhancement service for a target area in the area of the park production line according to the scheduling condition of the park production line and the communication service quality of the area of the park production line at the second time.

2. The method of claim 1, wherein the managing device obtaining, from the operator network, a communication quality of service for an area of the campus line at a first time, comprising:

the management equipment requests an operator network to open the communication service quality of the area where the park production line is located;

and the management equipment receives the communication service quality of the area where the park production line is located at the first time, which is opened by the operator network according to the request of the management equipment.

3. The method of claim 2, wherein the managing device requesting an operator network to open a communication quality of service for an area in which the campus line is located, comprises:

the management device sends a network capability opening request to a NEF network element of the operator network, wherein the capability opening request carries information for indicating an area where the park production line is located and information for requesting open communication service quality, the information for indicating the area where the park production line is located is converted into a corresponding cell identification list by the NEF network element, and at least one cell indicated by the cell identification list covers the area where the park production line is located;

The management device receives the communication service quality of the area where the open park production line is located at the first time according to the request of the management device, and the communication service quality comprises the following steps:

the management device receives a capability opening response returned by the operator network according to the capability opening request, wherein the capability opening response comprises a first communication service quality in each of M x N grids and information for indicating the first time, and an area where the park production line is located is divided into M x N grids, and M and N are integers greater than 1.

4. The method of claim 3, wherein the managing means processes the quality of communication service at a first time for the area of the campus line to predict the quality of communication service at a second time for the area of the campus line using an industrial large model, comprising:

the management device inputs the first communication service quality in each of the m×n grids to the industrial large model to obtain the second communication service quality in each of the m×n grids after a preset duration, wherein the preset duration after the first time is the second time.

5. The method of claim 4, wherein the managing device inputs the first communication service quality in each of the M x N grids to the industrial large model to obtain the second communication service quality in each of the M x N grids after a preset duration output by the industrial large model, wherein the convolutional neural network model of the industrial large model comprises:

the management device maps a first communication service quality in each of the m×n grids to a first grid image, wherein the first grid image includes m×n grids, each of the m×n grids in the first grid image corresponds to one of the m×n grids, and a gray value filled in each of the m×n grids in the first grid image represents the first communication service quality of the corresponding one of the grids;

the management device inputs the first grid image to the convolutional neural network model to obtain a second grid image output by the convolutional neural network model, wherein the second grid image comprises M x N grids, each grid of the M x N grids in the second grid image corresponds to one grid of the M x N grids, and a gray value filled in each grid of the M x N grids in the second grid image represents the second communication service quality of one grid corresponding to the grid;

The management device inversely maps the second grid image to a second quality of communication service within each of the M x N grids.

6. The method according to claim 4, wherein the recursive neural network model of the industrial large model has an input data format of outputting L items of data, where L is greater than or equal to m×n, and the management device inputs a first communication service quality in each of the m×n grids to the industrial large model, to obtain a second communication service quality in each of the m×n grids after a preset duration, which is output by the industrial large model, and includes:

the management device takes the first communication service quality in each of the m×n grids as first data, and the management device fills the first data of the last L-m×n items to 0;

the management device inputs the first data of the first m×n items and the first data of the second L-m×n items into a recurrent neural network model to obtain second data of the L items output by the recurrent neural network model, wherein the second data of the first m×n items in the second data of the L items are second communication service quality in each of the grids of the m×n items, and the second data of the second L items in the second data of the second L items are 0.

7. The method of any one of claims 4-6, wherein the managing means requesting the carrier network to provide signal enhancement services for the target area in the area of the campus line based on the scheduling of the campus line and the communication service quality of the area of the campus line at the second time, comprising:

the management device determines at least one grid to be selected, wherein the second communication service quality of the grids is smaller than a communication service quality threshold value;

the management equipment determines at least one target grid from the at least one grids to be selected according to the production scheduling condition of the production line of the park, the production scheduling quantity of the production line in the area where the at least one target grid is located is larger than a production scheduling quantity threshold, and the area formed by the at least one target grid is the target area;

the management device requests the operator network to provide signal enhancement services for the target area.

8. The method of claim 7, wherein the managing device requesting the carrier network to provide signal enhancement services for the target area comprises:

the management device sends an enhanced service request to a NEF network element in the operator network, wherein the enhanced service request includes an identification of each of the at least one target grid, a second communication quality of service of each of the at least one target grid, information indicating the second time, and a cell for requesting signal enhanced service.

9. The method of claim 7, wherein the signal enhancement service refers to that a beam of the RAN device reflected by the RIS and a beam self-transmitted by the RAN device collectively irradiate an area where the signal enhancement service needs to be obtained.

10. An industrial large model-based auto-tuning line control system, the system comprising management equipment for a campus line, the system configured to: