CN115213907A - Operation and maintenance robot operation method and system based on edge calculation - Google Patents
Operation and maintenance robot operation method and system based on edge calculation Download PDFInfo
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Abstract
The invention provides an operation and maintenance robot operation method and system based on edge computing, which relate to the technical field of machine room operation and maintenance and comprise the steps of carrying out real-time edge computing analysis on collected data based on a visual algorithm model downloaded from a cloud platform, and determining state data of equipment to be maintained; judging whether the equipment to be maintained has faults or not according to the state data; and if so, correcting the equipment to be maintained according to the preset parameter index until the new state data of the equipment to be maintained is in accordance with the expectation so as to relieve the technical problems of real-time response of the operation and maintenance of the current equipment in the machine room, unstructured data processing and the like.
Description
Technical Field
The invention relates to the technical field of machine room operation and maintenance, in particular to an operation and maintenance robot operation method and system based on edge calculation.
Background
In the process of the robot in the machine room inspection operation and maintenance operation, most of data are transmitted to a central server or a cloud terminal for processing through a network, but when massive data calculation of machine room equipment is met, including some video, audio, picture and other unstructured data processing, enough or reliable network bandwidth is not available for transmitting the data to the cloud terminal, and the network is not stable enough or reliable enough, so that the system fails.
Disclosure of Invention
The invention aims to provide an operation and maintenance robot operation method and system based on edge calculation, so that the technical problems of real-time alarm of local equipment faults and processing of unstructured data such as video, audio and pictures and the like by the operation and maintenance of current machine room equipment are solved, and the quality and the efficiency of an operation and maintenance system are better facilitated.
In a first aspect, an embodiment of the present invention provides an operation and maintenance robot operation method based on edge calculation, which is applied to an operation and maintenance end, and the method includes:
performing real-time edge computing analysis on the acquired data based on a visual algorithm model downloaded from a cloud platform, and determining state data of the equipment to be maintained;
judging whether the equipment to be maintained has a fault according to the state data;
and if so, correcting the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained meet expectations.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the method further includes:
and sending the state data of the equipment to be maintained to the cloud platform so that the cloud platform updates the visual algorithm model.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the method further includes:
optimizing a filtering rule according to the weight relation between the state data output in the visual algorithm model and the collected data;
and processing the state data according to the optimized filtering rule, and sending the state data to the cloud platform.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the step of determining, according to the state data, whether the device to be maintained has a fault includes:
comparing each state data in the state combination of the equipment to be maintained with a state threshold, wherein the state combination is the combination of one or more items of state data;
if the state data exceeds a preset state threshold, counting alarm values of state combinations corresponding to the state data;
and judging whether the equipment to be maintained has faults or not according to whether the alarm value corresponding to the state combination exceeds a preset alarm threshold value or not.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the step of performing real-time edge computing analysis on the acquired data based on a visual algorithm model downloaded from a cloud platform to determine state data of a device to be maintained includes:
and calculating and analyzing the collected data for representing the running state of the equipment to be maintained based on the visual algorithm model deployed at the edge end, and converting the data into the state data of the equipment to be maintained.
With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where before the step of performing real-time computational analysis on the collected data based on the visual algorithm model downloaded from the cloud platform, and determining the state data of the device to be maintained, the method further includes:
collecting the running state of the equipment to be maintained to obtain collected data, wherein the collected data comprises one or more of the following items: temperature data, sound data, panel data, light position data.
In a second aspect, an embodiment of the present invention further provides an operation and maintenance robot operating device based on edge calculation, which is applied to an operation and maintenance terminal, and the device includes:
the determining module is used for carrying out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform and determining the state data of the equipment to be maintained;
the judging module is used for judging whether the equipment to be maintained has faults or not according to the state data;
and if the equipment to be maintained exists, the correction module corrects the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained accords with expectations.
In a third aspect, an embodiment of the present invention further provides an operation and maintenance robot operating system based on edge computing, including an operation and maintenance terminal, a collection terminal, and a cloud platform, where the system includes:
the acquisition end acquires the acquisition data of the equipment to be maintained;
the operation and maintenance terminal carries out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform, and determines state data of the equipment to be maintained; judging whether the equipment to be maintained has a fault according to the state data; and if the equipment to be maintained exists, correcting the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained accords with the expectation.
In a fourth aspect, an embodiment provides an electronic device, including a memory and a processor, where the memory stores a computer program executable on the processor, and the processor implements the steps of the method described in any one of the foregoing embodiments when executing the computer program.
In a fifth aspect, embodiments provide a machine-readable storage medium having stored thereon machine-executable instructions that, when invoked and executed by a processor, cause the processor to carry out the steps of the method of any preceding embodiment.
The embodiment of the invention provides an operation and maintenance robot operation method and system based on edge calculation, wherein a visual algorithm model originally located at a cloud end is downloaded and deployed at an operation and maintenance end, so that the operation and maintenance end can automatically perform real-time edge calculation analysis on collected data of equipment to be maintained to obtain state data, and the fault condition of the equipment to be maintained is judged according to the state data; the state data does not need to be downloaded from the cloud, the time for the cloud to send the state data back to the operation and maintenance terminal is saved, and the working efficiency of remote cooperation of the operation and maintenance terminal is improved.
Particularly, the robot edge computing and operation and maintenance cloud platform are complementary and developed in a mutually coordinated manner, so that the efficiency and quality of operation and maintenance are improved to a greater extent.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
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 embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an operation and maintenance robot operation method based on edge calculation according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a machine room cooperative operation and maintenance robot system according to an embodiment of the present invention;
fig. 3 is a schematic view of a scene application of an operation and maintenance robot operation method based on edge calculation according to an embodiment of the present invention;
fig. 4 is a functional module schematic diagram of an operation and maintenance robot working device based on edge calculation according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware architecture of an electronic device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent 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.
The robot that patrols and examines obtains certain popularization and application at the IDC computer lab at present, but the most is the daily work of patrolling and examining of being applied to the computer lab, has some other functions in the daily fortune of computer lab, for example reception, supplementary fortune dimension, emergent etc. and the robot is in cooperation fortune dimension personnel operation, alleviates staff's frequency of labour, intensity, reduces fortune dimension cost aspect, has huge excavatability.
The existing machine room inspection robot system combines real-time video acquisition, sound acquisition, safety inspection and abnormal condition detection through an autonomous walking robot to realize real-time dynamic detection of machine room equipment. The function is only one mobile remote monitoring tool.
However, the services of the machine room are complex and multi-aspect, for example, for the management and cooperation problems of the maintainers entering the machine room, and some low-frequency service applications, such as emergency management problems, reception problems of the benchmarking machine room, and the like, these service requirements cannot be met by the existing inspection robot. In addition, in the inspection application of the robot, the function of the existing robot is single, so that the inspection application is emphasized, but due to the influence of the environment of a machine room and the complexity of equipment of the machine room, the algorithm applied to the robot at present is limited by various factors, and efficient remote cooperation cannot be realized.
Based on this, the operation and maintenance robot operation method and system based on edge calculation provided by the embodiment of the invention can save the time for sending the state data from the cloud and improve the operation efficiency of remote cooperation by calculating the state data by the operation and maintenance terminal.
To facilitate understanding of the embodiment, first, a detailed description is given of an operation and maintenance robot operation method based on edge computing according to the embodiment of the present invention, where the method is applicable to an operation and maintenance terminal, and as shown in fig. 2, the operation and maintenance terminal is connected to a cloud platform and a collection terminal respectively.
Fig. 1 is a flowchart of an operation and maintenance robot operation method based on edge calculation according to an embodiment of the present invention.
Referring to fig. 1, the method includes the following steps:
and S102, performing real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform, and determining the state data of the equipment to be maintained.
As can be seen from fig. 2, the cloud platform may be understood as a cloud server, and is used to issue a visual algorithm model and a micro service, and the operation and maintenance end uploads relevant data of the device to be maintained to the cloud platform, such as collected data and status data. The visual algorithm model may be understood as an algorithm model having a visual conversion function, and may be a model capable of converting visual type data into numerical type data, and is not limited to a specific algorithm type.
And step S104, judging whether the equipment to be maintained has faults or not according to the state data.
The state data can be understood as data embodied by the working state of the equipment to be maintained, namely, the working state of the equipment to be maintained can be known through the state data, and the monitoring and maintenance effect of the equipment to be maintained is further realized.
And S106, if the new state data of the equipment to be maintained is consistent with the expectation, correcting the equipment to be maintained according to the preset parameter index.
It can be understood that, if the equipment to be maintained has a fault, the equipment to be maintained is corrected and maintained according to the preset parameter index, so that the new state data corresponding to the maintained equipment meets the requirement; the preset parameter index can be understood as a parameter index of normal operation corresponding to each device to be maintained.
In a preferred embodiment of practical application, the visual algorithm model originally located at the cloud is downloaded and deployed at the operation and maintenance end, so that the operation and maintenance end can perform real-time edge calculation analysis on the collected data of the equipment to be maintained by itself to obtain state data, and the fault condition of the equipment to be maintained is judged according to the state data; the state data does not need to be downloaded from the cloud, the time for the cloud to send the state data back to the operation and maintenance terminal is saved, and the working efficiency of remote cooperation of the operation and maintenance terminal is improved.
In some embodiments, the visual algorithm model of the cloud platform may be optimized by using the calculated state data of the operation and maintenance terminal, so that the operation and maintenance terminal can perform accurate calculation of the state data according to the latest visual algorithm model, and the method provided by the above embodiments further includes:
step 1.1), sending the state data of the equipment to be maintained to the cloud platform so as to enable the cloud platform to update the visual algorithm model.
The machine learning-based visual algorithm model is generally deployed at the cloud end, the edge end in the operation and maintenance end transmits key data of equipment to the cloud end in real time, the cloud platform continuously conducts iterative training through the data and continuously evolves and improves to form a new visual algorithm model, the new visual algorithm model is timely downloaded by the edge end, the visual algorithm analyzes the acquired data, and the acquired data, state data and fault results are fed back to the cloud platform to help to iterate the new model. This is a cyclic, continuous spiral lifting process.
In some embodiments, the data to be uploaded may be accurately filtered to reduce transmission traffic cost and cloud storage cost, and the method further includes:
and 2.1) optimizing a filtering rule according to the weight relation between the state data output in the visual algorithm model and the collected data.
And 2.2) processing the state data according to the optimized filtering rule, and sending the state data to the cloud platform.
The key data which greatly influences the equipment to be maintained can be filtered out according to the weight relation between the state data and the collected data, namely, the less important state data does not need to be uploaded to a cloud terminal, so that the transmission flow and the saving of the storage cost of the cloud terminal are ensured.
In some embodiments, whether the device to be maintained has a fault is determined according to the overall condition of one or more combinations of the state data, so as to ensure the reliability of fault determination, and step S104 includes:
and 3.1) comparing each state data in the state combination of the equipment to be maintained with a state threshold value.
Wherein the state combination is a combination of one or more of the state data. For example, status data may include temperature status, lamp status, sound status, and the like, with possible combinations of status including: the combination of the first, temperature state, combination of the second, lamp position state, combination of the third, sound state, combination of the fourth, temperature state, lamp position state, combination of the fifth, temperature state, lamp position state and sound state, etc.
And 3.2) counting the alarm values of the state combinations corresponding to the state data if the state data exceeds a preset state threshold value.
It should be noted that, each state data is compared with the corresponding threshold, and for the combination five, if the temperature state and the lamp position state therein both exceed their respective thresholds, the alarm value corresponding to the combination five is two; and if the temperature state, the lamp position state and the sound state in the fifth combination exceed the respective threshold values, the alarm value corresponding to the fifth combination is three.
And 3.3) judging whether the equipment to be maintained has faults or not according to whether the alarm value corresponding to the state combination exceeds a preset alarm threshold value or not.
On the basis of the foregoing embodiment, if the preset alarm threshold corresponding to the fifth combination is three, when the state data in the fifth combination, that is, the temperature state, the lamp position state, and the sound state, are all faulty, it is determined that the davis device has a fault.
As an alternative embodiment, the comparison may be performed through multiple dimensions to determine whether the device to be maintained actually fails. Taking temperature data as an example, comparing the temperature data with a warning threshold value which is input in advance, if the temperature data exceeds the threshold value, displaying that the equipment to be maintained needs to focus on the temperature, then comparing equipment sound during working, and then comparing a status indicator lamp during working of the equipment; if the lamp position state is that the lamp is turned off or the lamp is turned on, or the color is abnormal or the flicker is abnormal, the above conditions can be input into the fault detection model, and the fault probability of the equipment is judged, for example, the fault detection model adopts a 3-class algorithm model, the fault detection model is divided into 3 grades, 1 item of warning is provided, the fault probability is 30-50%, 2 items of warning are provided, the fault probability is 60-70%, and 3 items of warning information are provided, the fault probability is 90-100%, and the important attention needs to be paid, and the fault judgment information embodied in the combined algorithm is displayed.
In some embodiments, the maintenance end includes an edge end, and the edge end can calculate the state data according to the visual algorithm model downloaded from the cloud, so as to reduce the time for returning the state data from the cloud, and step S102 can also be implemented by the following steps, including:
and 4.1) calculating and analyzing the collected data for representing the running state of the equipment to be maintained based on the visual algorithm model deployed at the edge end, and converting the data into state data of the equipment to be maintained.
The collected data may be understood as a visual data type, such as an image data type.
In some embodiments, before step S102, the operation state may be collected, and the method further includes, for example:
step 5.1), collecting the running state of the equipment to be maintained to obtain collected data, wherein the collected data comprises one or more of the following items: temperature data, sound data, panel data, light position data.
In the practical application process, the equipment to be maintained in the running state can be shot, and then the collected data which can embody the characteristics are determined.
As an alternative embodiment, the field service constructor always encounters a problem in the equipment maintenance operation, and calls the robot and obtains the remote knowledge base assistance from the robot system. The robots provide internal and external knowledge base collaboration including equipment specific parameters, performance, fault codes, maintenance methods, and the like. The internal knowledge base is connected with the intranet and provided in the enterprise system. The external knowledge base needs to apply for external network connection such as the internet, and provides wider knowledge base data sharing including equipment suppliers. The remote assistance can be understood as that remote video conference conversation is realized through a remote video and audio technology, and remote experts and management personnel are searched for assistance on site.
The robot edge computing of the embodiment of the invention can process and analyze data in real time or more quickly, so that the data processing is more reliable, and the robot edge computing is not an external data center or a cloud, thereby shortening the delay time and greatly reducing the expenditure budget on the cost pre-computing. Data management solutions for enterprises on a robot centric device cost significantly less than cloud and data centric networks. Meanwhile, through the filtration to state data, reduce network flow, can solve along with the increase of computer lab thing networking equipment quantity, data generation continues to increase with the speed of creating the record. As a result, network bandwidth becomes more limited. In addition, the method and the device can continuously learn through edge calculation, adjust the model according to the requirements of the user, bring personalized interaction experience, reduce delay level, enable the application program to run more efficiently and more quickly, and improve application program efficiency.
As shown in fig. 4, an embodiment of the present invention provides an operation and maintenance robot working apparatus based on edge calculation, where the apparatus includes:
the determining module is used for carrying out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform and determining the state data of the equipment to be maintained;
the judging module is used for judging whether the equipment to be maintained has faults or not according to the state data;
and if the equipment to be maintained exists, the correction module corrects the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained accords with expectations.
An embodiment of the present invention further provides an operation and maintenance robot operating system based on edge computing, as shown in fig. 2, including an operation and maintenance end, an acquisition end, and a cloud platform, where the system includes:
the acquisition end acquires the acquisition data of the equipment to be maintained;
the operation and maintenance terminal carries out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform, and determines state data of the equipment to be maintained; judging whether the equipment to be maintained has a fault according to the state data; and if so, correcting the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained meet expectations.
The cloud platform is responsible for issuing a visual algorithm model and micro-services, and the operation and maintenance end uploads related data to the cloud platform; the acquisition end can acquire data of field equipment through a sensor, a camera and other equipment of the robot and input the data into the operation and maintenance end, and the operation and maintenance end can control the output of the acquisition end.
The operation and maintenance terminal comprises an edge controller layer, an edge gateway layer and an edge cloud layer:
(1) Edge controller layer
The edge controller is connected with various field devices at the edge side of the industrial internet, performs conversion and adaptation of industrial protocols, is uniformly connected into an edge computing network, encapsulates the device capability in a service form, and realizes communication connection between production devices in physics and logic. The edge controller hardware architecture design adopts a distributed heterogeneous computing platform, generally adopts a heterogeneous computing system structure, supports full distributed control and cooperative operation and seamless integration of various controllers, and is also a mainstream implementation scheme realized by various real-time embedded hardware platforms at present; on the premise of meeting the real-time requirement of hardware, the multi-physical kernel is combined with the support of a virtualization technology to realize the running of real-time and non-real-time tasks or operating systems on the same hardware platform, meet the requirements of system diversification and portability, and improve the safety, reliability and flexibility of the whole platform system and the utilization efficiency of resources; and a mode of combining a multi-task scheduling mechanism and a multi-thread scheduling mechanism which are separated in time and space with a transformation optimization scheduling algorithm is applied to realize a task scheduling mechanism.
Aiming at the operation and maintenance task needing to adopt multi-controller cooperation for inspection, the edge controller adopts a cooperation control strategy and a control consistency protocol, and combines a borderless networked dynamic simulation technology, so that the robustness and the real-time performance of the intelligent control system during network information exchange in a field interference environment are improved, and the self-adaptive cooperation control of the multi-controller in a dynamic environment is realized. Meanwhile, the flexibility of the control system is improved by adopting a software-defined networked intelligent control system technology.
(2) Edge gateway layer
The edge gateway is an edge computing device with the capabilities of edge computing, process control, motion control, machine vision, field data acquisition and industrial protocol analysis. The edge gateway can adapt to the complex severe environment of an industrial field, meets the requirements of access and data analysis of industrial equipment such as domestic mainstream controllers, industrial robots, intelligent sensors and the like, and supports edge end data operation and pushes data to an industrial internet platform through the internet.
The edge gateway can convert the standard or private communication protocol of various field industrial equipment and devices adopted and applied systems into communication protocols such as standard OPC UA and the like, so that an upper system and an industrial Internet platform can adopt a unified protocol and an information model to communicate with different equipment and systems, system integration is facilitated, and functions of remote monitoring, fault diagnosis, configuration downloading, remote management and the like are realized.
(3) Cloud layer of edge
The edge cloud is a single or a plurality of distributed cooperative servers on the edge side, realizes specific functions through locally deployed applications, provides elastically expanded network, computing and storage capabilities, meets the requirements on reliability, real-time performance, safety and the like, and is an important link for realizing deep fusion of an IT technology and an OT technology.
On one hand, a model trained in the cloud end on the basis of machine learning offline is deployed to the edge cloud, edge intelligence is synchronized by regularly updating a model algorithm, so that emergency faults can be alarmed locally in time, and meanwhile, some relevant parameter indexes can be corrected in real time. On the other hand, according to the weight relation between the output and the characteristics in the model, the filtering rule of the data uploaded by the terminal is optimized, so that the flow cost and the cloud storage cost are reduced.
In the actual application process, as shown in fig. 3, the edge supports the cloud application to issue and manage; supporting a remote end to carry out unified scheduling on edge node services; and multi-dimensional cloud edge coordination capacity such as edge data stream analysis is supported.
The operation and maintenance robot operation system based on edge computing integrates artificial intelligence, cloud computing, big data, a multi-sensor fusion technology, a laser navigation positioning technology, an internet of things technology and the like by taking an intelligent inspection robot based on human-computer cooperation as a core. The human-computer cooperation is taken as a core, and environment perception, dynamic decision, behavior control and alarm devices and image perception are integrated. The intelligent inspection system has the capabilities of autonomous perception, autonomous walking, autonomous protection, autonomous identification and the like, and can realize all-weather, all-directional and all-autonomous intelligent inspection and monitoring. The device is compatible with different industrial protocols and different data formats in an operation and maintenance and rapid access mode, and the local computing service with low delay, low cost, high availability and easy expansion is provided. Meanwhile, the method is combined with cloud big data, an intelligent learning model and the like, an optimal data application mode is provided, and a three-in-one intelligent industrial internet system of cloud side ends (a cloud platform, edge computing and equipment ends) is created.
In this embodiment, the electronic device may be, but is not limited to, a Computer device with analysis and processing capabilities, such as a Personal Computer (PC), a notebook Computer, a monitoring device, and a server.
As an exemplary embodiment, referring to fig. 5, the electronic device 110 includes a communication interface 111, a processor 112, a memory 113, and a bus 114, wherein the processor 112, the communication interface 111, and the memory 113 are connected by the bus 114; the memory 113 is used for storing computer programs that support the processor 112 to execute the above-mentioned methods, and the processor 112 is configured to execute the programs stored in the memory 113.
A machine-readable storage medium as referred to herein may be any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the machine-readable storage medium may be: a RAM (random Access Memory), a volatile Memory, a non-volatile Memory, a flash Memory, a storage drive (e.g., a hard drive), any type of storage disk (e.g., an optical disk, a dvd, etc.), or similar storage medium, or a combination thereof.
The non-volatile medium may be non-volatile memory, flash memory, a storage drive (such as a hard drive), any type of storage disk (such as an optical disk, dvd, etc.), or similar non-volatile storage medium, or a combination thereof.
It can be understood that, for the specific operation method of each functional module in this embodiment, reference may be made to the detailed description of the corresponding step in the foregoing method embodiment, and no repeated description is provided herein.
The computer-readable storage medium provided in the embodiments of the present invention stores a computer program, and when executed, the computer program code may implement the method described in any of the above embodiments, and for specific implementation, reference may be made to the method embodiment, which is not described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.
Claims (10)
1. An operation and maintenance robot operation method based on edge calculation is applied to an operation and maintenance end, and comprises the following steps:
performing real-time edge calculation analysis on the acquired data based on a visual algorithm model downloaded from a cloud platform, and determining state data of the equipment to be maintained;
judging whether the equipment to be maintained has a fault according to the state data;
and if the equipment to be maintained exists, correcting the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained accords with the expectation.
2. The method of claim 1, further comprising:
and sending the state data of the equipment to be maintained to the cloud platform so that the cloud platform updates the visual algorithm model.
3. The method according to claim 1 or 2, characterized in that the method further comprises:
optimizing a filtering rule according to the weight relation between the state data output in the visual algorithm model and the acquired data;
and processing the state data according to the optimized filtering rule, and sending the state data to the cloud platform.
4. The method according to claim 1, wherein the step of determining whether the device to be maintained has a fault according to the status data comprises:
comparing each state data in the state combination of the equipment to be maintained with a state threshold, wherein the state combination is the combination of one or more items of state data;
if the state data exceeds a preset state threshold, counting alarm values of state combinations corresponding to the state data;
and judging whether the equipment to be maintained has faults or not according to whether the alarm value corresponding to the state combination exceeds a preset alarm threshold value or not.
5. The method of claim 1, wherein the step of performing real-time edge computing analysis on the collected data based on the visual algorithm model downloaded from the cloud platform to determine status data of the equipment to be maintained comprises:
and calculating and analyzing the collected data for representing the running state of the equipment to be maintained based on the visual algorithm model deployed at the edge end, and converting the data into the state data of the equipment to be maintained.
6. The method of claim 2, wherein prior to the step of performing real-time computational analysis on the collected data based on the visual algorithm model downloaded from the cloud platform to determine status data of the equipment to be maintained, the method further comprises:
acquiring the running state of the equipment to be maintained to obtain acquired data, wherein the acquired data comprises one or more of the following items: temperature data, sound data, panel data, light position data.
7. An operation and maintenance robot working device based on edge calculation is characterized in that the device is applied to an operation and maintenance end and comprises:
the determining module is used for carrying out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform and determining the state data of the equipment to be maintained;
the judging module is used for judging whether the equipment to be maintained has faults or not according to the state data;
and if the equipment to be maintained exists, the correction module corrects the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained accords with expectations.
8. An operation and maintenance robot operation system based on edge computing is characterized by comprising an operation and maintenance end, an acquisition end and a cloud platform, and the system comprises:
the acquisition end acquires the acquisition data of the equipment to be maintained;
the operation and maintenance terminal carries out real-time edge calculation analysis on the acquired data based on the visual algorithm model downloaded from the cloud platform, and determines the state data of the equipment to be maintained; judging whether the equipment to be maintained has a fault according to the state data; and if so, correcting the equipment to be maintained according to preset parameter indexes until the new state data of the equipment to be maintained meet expectations.
9. An electronic device comprising a memory, a processor, and a program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1 to 6 when executing the program.
10. A computer-readable storage medium, characterized in that a computer program is stored in the readable storage medium, which computer program, when executed, carries out the method of any one of claims 1-6.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109927025A (en) * | 2017-12-18 | 2019-06-25 | 广州供电局有限公司 | Patrol dimension robot control method, device, computer equipment and storage medium |
| CN110806730A (en) * | 2019-10-22 | 2020-02-18 | 重庆川仪自动化股份有限公司 | Big data operation and maintenance platform, server and storage medium |
| CN111267079A (en) * | 2018-12-05 | 2020-06-12 | 中国移动通信集团山东有限公司 | Intelligent inspection robot inspection method and device |
| CN112307076A (en) * | 2019-08-02 | 2021-02-02 | 深圳中集智能科技有限公司 | Production equipment operation and maintenance system and method based on cloud and end fusion |
| CN112463393A (en) * | 2020-12-14 | 2021-03-09 | 国网辽宁省电力有限公司抚顺供电公司 | Power distribution Internet of things edge computing architecture design method based on Mongo cluster technology |
| US20210191760A1 (en) * | 2019-12-23 | 2021-06-24 | UiPath, Inc. | On-demand cloud robots for robotic process automation |
| CN113254529A (en) * | 2021-05-12 | 2021-08-13 | 兰州兰石集团有限公司 | Industry thing networking platform based on edge calculation and HiTSDB storage |
| CN113572625A (en) * | 2020-04-28 | 2021-10-29 | 中国移动通信集团浙江有限公司 | Fault early warning method, early warning device, equipment and computer medium |
| US20220114044A1 (en) * | 2020-10-14 | 2022-04-14 | UiPath, Inc. | Anomaly detection and self-healing for robotic process automation via artifical intelligence / machine learning |
| CN114826881A (en) * | 2022-04-15 | 2022-07-29 | 北京科杰科技有限公司 | Intelligent operation and maintenance method based on correlation analysis and computer readable storage medium |
-
2022
- 2022-08-05 CN CN202210936942.5A patent/CN115213907A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109927025A (en) * | 2017-12-18 | 2019-06-25 | 广州供电局有限公司 | Patrol dimension robot control method, device, computer equipment and storage medium |
| CN111267079A (en) * | 2018-12-05 | 2020-06-12 | 中国移动通信集团山东有限公司 | Intelligent inspection robot inspection method and device |
| CN112307076A (en) * | 2019-08-02 | 2021-02-02 | 深圳中集智能科技有限公司 | Production equipment operation and maintenance system and method based on cloud and end fusion |
| CN110806730A (en) * | 2019-10-22 | 2020-02-18 | 重庆川仪自动化股份有限公司 | Big data operation and maintenance platform, server and storage medium |
| US20210191760A1 (en) * | 2019-12-23 | 2021-06-24 | UiPath, Inc. | On-demand cloud robots for robotic process automation |
| CN113572625A (en) * | 2020-04-28 | 2021-10-29 | 中国移动通信集团浙江有限公司 | Fault early warning method, early warning device, equipment and computer medium |
| US20220114044A1 (en) * | 2020-10-14 | 2022-04-14 | UiPath, Inc. | Anomaly detection and self-healing for robotic process automation via artifical intelligence / machine learning |
| CN112463393A (en) * | 2020-12-14 | 2021-03-09 | 国网辽宁省电力有限公司抚顺供电公司 | Power distribution Internet of things edge computing architecture design method based on Mongo cluster technology |
| CN113254529A (en) * | 2021-05-12 | 2021-08-13 | 兰州兰石集团有限公司 | Industry thing networking platform based on edge calculation and HiTSDB storage |
| CN114826881A (en) * | 2022-04-15 | 2022-07-29 | 北京科杰科技有限公司 | Intelligent operation and maintenance method based on correlation analysis and computer readable storage medium |
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