CN116778597A - Fan inspection robot and fan inspection system - Google Patents
Fan inspection robot and fan inspection system Download PDFInfo
- Publication number
- CN116778597A CN116778597A CN202310523863.6A CN202310523863A CN116778597A CN 116778597 A CN116778597 A CN 116778597A CN 202310523863 A CN202310523863 A CN 202310523863A CN 116778597 A CN116778597 A CN 116778597A
- Authority
- CN
- China
- Prior art keywords
- fan
- inspection
- communication
- inspection robot
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007689 inspection Methods 0.000 title claims abstract description 185
- 238000004891 communication Methods 0.000 claims abstract description 153
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 27
- 238000012423 maintenance Methods 0.000 claims description 21
- 238000006243 chemical reaction Methods 0.000 claims description 19
- 238000000034 method Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 8
- 230000002159 abnormal effect Effects 0.000 description 13
- 238000005516 engineering process Methods 0.000 description 9
- 230000007547 defect Effects 0.000 description 5
- 238000007726 management method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000005856 abnormality Effects 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000002688 persistence Effects 0.000 description 1
- 238000009877 rendering Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/20—Checking timed patrols, e.g. of watchman
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W36/00—Hand-off or reselection arrangements
- H04W36/24—Reselection being triggered by specific parameters
- H04W36/30—Reselection being triggered by specific parameters by measured or perceived connection quality data
- H04W36/305—Handover due to radio link failure
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Manipulator (AREA)
Abstract
The application discloses a fan inspection robot and a fan inspection system, and belongs to the technical field of fan inspection. Wherein, fan inspection robot includes: the system comprises a controller, a communication module, an image acquisition module and an artificial intelligence module; the controller is connected with the communication module, the image acquisition module and the artificial intelligence module; the controller is used for controlling the fan inspection robot to operate according to a set mode; the communication module is used for communicating based on a first communication mode or a second communication mode; the image acquisition module is used for receiving the inspection image, and the artificial intelligence module is used for determining the fault type of the fan according to the inspection image. The technical scheme provided by the application effectively solves the problems of low communication efficiency, poor multi-robot coordination capability, limited application scene and low inspection efficiency of the fan inspection robot.
Description
Technical Field
The application belongs to the technical field of fan inspection, and particularly relates to a fan inspection robot and a fan inspection system.
Background
Through the fan inspection, the running state of fan equipment can be known at any time, the abnormal condition of the equipment can be found in time, so that effective measures can be quickly taken to treat the abnormal condition, and the normal running and long-term stability of the fan are ensured.
The frequency of manual inspection and inspection points are insufficient, effective identification means are lacked for some abnormal conditions, time and labor are wasted, the efficiency is low, the inspection efficiency of the fan inspection robot can be improved, and the labor and time cost is reduced. However, the communication mode of the conventional fan inspection robot is single, so that the communication efficiency is low, various requirements of users cannot be met, and the conventional fan inspection robot cannot be suitable for complex application scenes; in addition, the existing fan inspection robot has poor coordination capability of multiple robots in the inspection process, and cannot realize simultaneous inspection at multiple places; and the inspection judgment is carried out by collecting videos and pictures through the robot and uploading the videos and pictures to the monitoring end, and then the monitoring end determines whether the problems exist or not in a manual judgment mode, so that the inspection efficiency is still low.
In summary, the problems of lower communication efficiency, poor coordination capability of multiple robots, limited application scenes and low inspection efficiency of the fan inspection robot exist in the prior art.
Disclosure of Invention
Aiming at the defects of the related art, the application provides a fan inspection robot and a fan inspection system, and aims to solve the problems of low communication efficiency, poor multi-robot coordination capability, limited application scene and low inspection efficiency of the fan inspection robot in the related art.
The technical scheme is as follows:
according to one aspect of the application, a fan inspection robot includes: the system comprises a controller, a communication module, an image acquisition module and an artificial intelligence module; the controller is connected with the communication module, the image acquisition module and the artificial intelligence module; the controller is used for controlling the fan inspection robot to operate according to a set mode; the communication module is used for communicating based on a first communication mode or a second communication mode; the image acquisition module is used for receiving the inspection image, and the artificial intelligence module is used for determining the fault type of the fan according to the inspection image.
Optionally, the fan inspection robot further comprises a sensing module; the sensing module is used for acquiring communication parameters of the fan inspection robot.
Optionally, the communication module includes a conversion control unit, a first communication unit, and a second communication unit; the first communication unit is used for communicating based on the first communication mode, and the second communication unit is used for communicating based on the second communication mode; the conversion control unit is used for managing the first communication unit and the second communication unit, so that the fan inspection robot converts the communication modes between the first communication mode and the second communication mode.
Optionally, the image acquisition module comprises a camera unit; the camera unit is used for acquiring the inspection image aiming at the fan.
Optionally, the artificial intelligence module comprises a fan operation environment state database; the fan operation and maintenance environment state database is used for matching fault types and uploading alarms.
Optionally, the fan operation environment state database is built by building a globally unified data set or view through various tools and processing logic based on the scattered local data.
Optionally, the artificial intelligence module processes the inspection image based on an image recognition technology, and recognizes the fault type of the fan.
Optionally, the first communication mode is short-range wireless communication, and the second communication mode is long-range wireless communication.
According to one aspect of the application, a fan inspection system includes: the upper computer, the inspection track and at least one fan inspection robot are arranged; the upper computer is used for controlling the fan inspection robot.
Optionally, the upper computer comprises a cooperative control unit and a wireless communication unit; the cooperative control unit is used for preparing control logic for executing the inspection task of each fan inspection robot and determining the inspection range of each fan inspection robot; the wireless communication unit is used for sending the control logic and the inspection range generated by the cooperative control unit to each fan inspection robot.
Optionally, the inspection track is laid according to the working position of each fan inspection robot.
The application has the following beneficial effects:
the fan inspection robot comprises a controller, a communication module, an image acquisition module and an artificial intelligent module, wherein the communication module is used for communication based on a first communication mode or a second communication mode, can intelligently switch to one of the first communication mode and the second communication mode for communication according to surrounding environment, communication parameters of the fan inspection robot and the like, overcomes the defect of single communication mode of the fan inspection robot, realizes the organic integration of the first communication mode and the second communication mode, improves the communication efficiency, can meet more requirements of users, and widens the application scene of the fan inspection robot; the artificial intelligent module of the fan inspection robot automatically identifies abnormal conditions according to inspection images through an artificial intelligent technology, and the inspection of the abnormal conditions is not needed by relying on human eyes and personal experience, so that the inspection efficiency and the identification accuracy of the abnormal conditions are greatly improved; the fan inspection robot provided by the application can form a fan inspection system comprising a plurality of fan inspection robots working cooperatively, and based on an upper computer and control logic, the track, the data interface and the scheduling logic of each fan inspection robot are unified, so that the fan inspection system has the capabilities of integrating multiple brands of robots and collecting multiple source data, realizes simultaneous inspection of multiple places of multiple robots, enhances the capability of the multiple robots to work cooperatively in the inspection process, and can be suitable for more and more complex application scenes. The technical scheme provided by the application effectively solves the problems of low communication efficiency, poor multi-robot coordination capability, limited application scene and low inspection efficiency of the fan inspection robot.
Drawings
Fig. 1 is a schematic structural diagram of a fan inspection robot according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a fan inspection system according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an upper computer in an exemplary embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application. In addition, the technical features of the embodiments of the present application described below may be combined with each other as long as they do not collide with each other.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
Referring to fig. 1, an embodiment of the present application provides a fan inspection robot 100, where the fan inspection robot 100 includes: a controller 110, a communication module 120, an image acquisition module 130, and an artificial intelligence module 140.
The controller 110 is connected to the communication module 120, the image acquisition module 130, and the artificial intelligence module 140, and the controller 110 is configured to control the fan inspection robot 100 to operate according to a set manner.
The communication module 120 is configured to communicate based on the first communication mode or the second communication mode. For example, the first communication mode may be a short-range wireless communication, and the second communication mode may be a long-range wireless communication, which is not particularly limited herein.
In one possible implementation, the communication module 120 includes a conversion control unit 121, a first communication unit 122, and a second communication unit 123. The first communication unit 122 is configured to communicate based on a first communication mode, the second communication unit 123 is configured to communicate based on a second communication mode, and the conversion control unit 121 is configured to manage the first communication unit 122 and the second communication unit 123, so that the fan inspection robot 100 converts the communication mode between the first communication mode and the second communication mode.
Wherein the switching control unit 121 switches the communication mode to one of the first communication mode and the second communication mode according to the surrounding environment, the communication condition, and the like. Taking the first communication mode as the near-field communication and the second communication mode as the far-field communication as an example, when the communication data amount is small, the conversion control unit 121 may select the near-field communication; when larger data such as an image or recorded data is transmitted, the conversion control unit 121 may select remote wireless communication; the initial setting of the conversion control unit 121 may be to use short-range wireless communication, and when the number of communication failures exceeds a predetermined threshold, the conversion control unit 121 converts to long-range wireless communication, indicating that the surrounding environment is complex; the conversion control unit 121 periodically monitors whether data transmission is clear in the short-range wireless communication mode, and if so, performs conversion to short-range wireless communication to reduce power consumption.
In one possible implementation manner, the fan inspection robot 100 further includes a sensing module 150, and the sensing module 150 is configured to obtain the communication parameters of the fan inspection robot 100, and provide a basis for the conversion of the communication mode for the conversion control unit 121.
The communication parameters may be communication data volume, influence of the surrounding environment on the data transmission rate, and the like, which are not particularly limited herein.
In one possible implementation manner, the first communication manner is near-field wireless communication and is implemented based on a narrowband internet of things technology; the second communication mode is long-distance wireless communication and is realized based on wireless broadband technology.
The image acquisition module 130 is configured to receive the inspection image, and the artificial intelligence module 140 is configured to determine a fault type of the fan according to the inspection image.
The inspection image refers to image data shot by the fan in the inspection process, and can be used for inspecting the abnormality and the fault of the fan.
In one possible implementation, the image acquisition module 130 includes a camera unit for acquiring inspection images for the blower. The camera unit may be a CMOS camera or a CCD camera, and is not particularly limited herein.
In one possible implementation, the artificial intelligence module 140 is implemented based on an expert system, making decisions via pre-written rules and knowledge bases, identifying fan faults and giving solutions.
In one possible implementation, the artificial intelligence module 140 includes a fan operation and maintenance environment state database, where the fan operation and maintenance environment state database is used for matching and uploading alarms of fault types, for example, analyzing and processing the inspection images, calling a corresponding type exception type from the fan operation and maintenance environment state database to match, calling an equipment manual of the fault type according to the matching result, and guiding and uploading the equipment manual.
The fan operation and maintenance environment state database is used for storing and processing heterogeneous mass state data of multiple sources, wherein the state data are collected by the fan inspection robot 100 through sensing components such as a camera component, a high-precision sensor and the like, and for example, the state data can comprise components such as cabin oil equipment, pipelines, cables, fasteners and the like and operating environment state scenes thereof, and can also comprise data such as fan operation states, fault information, maintenance records, equipment manuals and the like.
The fan operation and maintenance environment state database can be used for model training and analysis, specifically, by performing model training and analysis on the state data in the fan operation and maintenance environment state database, the fan inspection robot 100 can more accurately sense and understand the operation environment of the fan inspection robot and make more intelligent decisions and actions.
Based on the scattered local data, a global unified data set or view is established through various tools and processing logic, so that a fan operation and maintenance environment state database is established, for example, mysql, oracle, hbase, hive and the like are used as data sources, cross-data source query is designed, and a multi-source heterogeneous data resource access mode is adapted, wherein the multi-source heterogeneous data resource access mode comprises configuration of the data sources, synchronization of data tasks, distribution and scheduling of data, ETL processing of the data and the like.
Wherein the scattered local data comprises data from different sensors of the fan inspection robot 100, and the processing logic comprises operations such as data cleaning, data conversion, data aggregation, data summarization, data calculation and the like. Tools include SQL queries, ETL tools, data warehouses, data mining, and the like.
The application process of the fan operation and maintenance environment state database can be divided into a front end UI layer, a presentation layer, a service layer, a data layer, a database layer, an operation environment and the like. Meanwhile, data interaction with a third party system is supported through the data access module.
The front-end UI layer is responsible for displaying the HTML page of the PC end.
The presentation layer is responsible for sending and receiving HTTP requests and rendering the template engine data.
The business layer mainly comprises main businesses such as factor management, personnel management, algorithm library, scheduling operation, system log and the like, wherein the factor management is responsible for maintaining abnormal type matching algorithm factors; personnel management is responsible for maintaining the availability, skill and state of abnormal type matching personnel and guiding the abnormal type; the algorithm library is responsible for computing and realizing various types of abnormal algorithms; scheduling the job to be responsible for timing synchronization of task data sources of other systems and triggering score ranking calculation; the system log is responsible for system runtime logging.
The data layer is responsible for caching of data and persistence of the data.
The database layer is responsible for managing and maintaining the database, such as backup, restore, optimization, etc.
The operating environment is responsible for providing the hardware, software environment, e.g., operating system, database software, etc., needed to run the database application.
Based on massive state data in the fan operation and maintenance environment state database, automatic analysis and processing of the data can be realized by means of artificial intelligence technology.
For example, in the process of operation and maintenance inspection of the fan, the inspection images are uploaded to a fan operation and maintenance environment state database, and then the images are automatically analyzed and identified by utilizing an image automatic identification technology, so that the operation state of the fan and whether faults exist or not are judged. If a fault exists, corresponding maintenance suggestions can be automatically generated according to data (such as an equipment manual) in a fan operation and maintenance environment state database and fed back to operation and maintenance personnel.
In one possible implementation, the artificial intelligence module 140 processes the inspection image based on image recognition techniques to identify the type of failure that the fan is experiencing. For example, the artificial intelligence module 140 is deployed with a trained deep neural network, can perform image recognition, and can output a corresponding fault type after inputting the inspection image.
Through the above embodiment, in the communication module 120, the conversion control unit 121 controls and manages the first communication unit 122 and the second communication unit 123, so that the fan inspection robot 100 can flexibly switch between different communication modes to meet different communication requirements, and the fan inspection robot can be suitable for complex application scenarios, and further improves communication efficiency, and the conversion control unit 121 can automatically select an optimal communication mode according to factors such as signal strength, network quality, communication parameters of the fan inspection robot, and the like, thereby ensuring reliability and stability of communication. The artificial intelligence module 140 automatically identifies the faults of the fan through image identification or other artificial intelligence technologies, so that the efficiency and accuracy of operation and maintenance of the fan are greatly improved, the workload and error rate of manual fault investigation are reduced, and the expert system can continuously learn and update the knowledge base, so that the identification and decision-making capability of the expert system is improved.
Referring to fig. 2, an embodiment of the present application provides a fan inspection system, including: the upper computer 200, the inspection track and at least one fan inspection robot 210 as described above, it should be noted that the inspection track is not shown in fig. 2, and the fan inspection system in fig. 2 includes three fan inspection robots 210 as an example, and the fan inspection system may also include one fan inspection robot 210 and two or more fan inspection robots 210.
The upper computer 200 is used for controlling the fan inspection robots 210, and the inspection tracks are paved according to the working positions of the fan inspection robots.
In one possible implementation, as shown in fig. 3, a schematic structural diagram of the upper computer 200 in an exemplary embodiment is shown.
In fig. 3, the upper computer 200 includes a cooperative control unit 201 and a wireless communication unit 203, where the cooperative control unit 201 is configured to determine a control logic of each fan inspection robot 210 to execute an inspection task, and determine an inspection range of each fan inspection robot 210; the wireless communication unit 203 is configured to send the control logic and the inspection range generated by the cooperative control unit 201 to each fan inspection robot 210.
The inspection track refers to a path or a route which needs to be walked in the inspection process of the fan inspection robot, namely the inspection route planning. When making the inspection track, consideration is needed. Through reasonable inspection track design, can improve the efficiency and the accuracy of inspection, reduce inspection cost and risk. The inspection track can be designed and paved according to actual conditions, and generally factors such as inspection range, target, frequency, time, safety, efficiency and feasibility are required to be considered so as to achieve the best inspection effect and cost effectiveness.
Through the above embodiment, the cooperative control unit 201 of the upper computer 200 formulates the control logic and the inspection range of the plurality of fan inspection robots 210 for simultaneous inspection on different tracks in different places, and sends the control logic and the inspection range to the fan inspection robots 210 through the wireless communication unit 203, so as to unify the data interfaces and the scheduling logic, control the plurality of fan inspection robots 210 to cooperatively and unify the inspection tasks, and further enable the fan inspection system to have the capability of integrating multiple brands of robots and collecting multiple source data, thereby overcoming the defects that the multi-fan inspection robots have poor cooperative inspection capability and cannot realize simultaneous inspection in multiple places.
Compared with the related art, the technical scheme of the application has the following beneficial effects:
1. the fan inspection robot comprises a controller, a communication module, an image acquisition module and an artificial intelligent module, wherein the communication module is used for communication based on a first communication mode or a second communication mode, can intelligently switch to one of the first communication mode and the second communication mode for communication according to surrounding environment, communication parameters of the fan inspection robot and the like, overcomes the defect of single communication mode of the fan inspection robot, realizes the organic integration of the first communication mode and the second communication mode, improves the communication efficiency, can meet more requirements of users, and widens the application scene of the fan inspection robot; the artificial intelligent module of the fan inspection robot automatically identifies abnormal conditions according to inspection images through an artificial intelligent technology, and the inspection of the abnormal conditions is not needed by relying on human eyes and personal experience, so that the inspection efficiency and the identification accuracy of the abnormal conditions are greatly improved; the fan inspection robot provided by the application can form a fan inspection system comprising a plurality of fan inspection robots working cooperatively, and based on an upper computer and control logic, the track, the data interface and the scheduling logic of each fan inspection robot are unified, so that the fan inspection system has the capabilities of integrating multiple brands of robots and collecting multiple source data, realizes simultaneous inspection of multiple places of multiple robots, enhances the capability of the multiple robots to work cooperatively in the inspection process, and can be suitable for more and more complex application scenes. The technical scheme provided by the application effectively solves the problems of low communication efficiency, poor multi-robot coordination capability, limited application scene and low inspection efficiency of the fan inspection robot.
2. In the communication module 120, the conversion control unit 121 controls and manages the first communication unit 122 and the second communication unit 123, so that the fan inspection robot 100 can flexibly switch between different communication modes to meet different communication requirements, and the fan inspection robot can be suitable for complex application scenes, and further improves the communication efficiency, and the conversion control unit 121 can automatically select an optimal communication mode according to factors such as signal strength, network quality, communication parameters of the fan inspection robot, and the like, so that the reliability and stability of communication are ensured. The artificial intelligence module 140 automatically identifies the faults of the fan through image identification or other artificial intelligence technologies, so that the efficiency and accuracy of operation and maintenance of the fan are greatly improved, the workload and error rate of manual fault investigation are reduced, and the expert system can continuously learn and update the knowledge base, so that the identification and decision-making capability of the expert system is improved.
3. The cooperative control unit 201 of the upper computer 200 formulates control logic and a patrol range for the simultaneous patrol of the plurality of fan patrol robots 210 on different tracks in different places, the control logic and the patrol range are sent to the fan patrol robots 210 through the wireless communication unit 203, the unified data interface and the scheduling logic control the plurality of fan patrol robots 210 to cooperatively and uniformly complete the patrol task, the fan patrol system is further enabled to have the capability of integrating multiple brands of robots and acquiring multiple source data, the defect that the multi-fan patrol robots are poor in cooperative patrol capability and cannot realize multi-place simultaneous patrol is overcome, and the system is applicable to more complex application scenes.
4. The fan operation and maintenance environment state database is constructed, the fan operation and maintenance environment state database can be used as a data source and a memory of artificial intelligence, data support and management are provided, a basis for data feature and model training is provided for the artificial intelligence, the fan inspection robot can realize automatic fault inspection, and the fault inspection accuracy and inspection efficiency can be improved.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the application and is not intended to limit the application, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (10)
1. A fan inspection robot, its characterized in that includes: the system comprises a controller, a communication module, an image acquisition module and an artificial intelligence module; the controller is connected with the communication module, the image acquisition module and the artificial intelligence module;
the controller is used for controlling the fan inspection robot to operate according to a set mode;
the communication module is used for communicating based on a first communication mode or a second communication mode;
the image acquisition module is used for receiving the inspection image;
the artificial intelligence module is used for determining the fault type of the fan according to the inspection image.
2. The blower inspection robot of claim 1, wherein the artificial intelligence module comprises a blower operational environment status database; the fan operation and maintenance environment state database is used for matching fault types and uploading alarms.
3. The blower inspection robot of claim 2, wherein the blower operational environment state database is built by building a globally unified dataset or view through various tools and processing logic based on decentralized local data.
4. The blower inspection robot of claim 1, wherein the communication module includes a conversion control unit, a first communication unit, and a second communication unit;
the first communication unit is used for communicating based on the first communication mode, and the second communication unit is used for communicating based on the second communication mode;
the conversion control unit is used for managing the first communication unit and the second communication unit, so that the fan inspection robot converts the communication modes between the first communication mode and the second communication mode.
5. The blower inspection robot of claim 1, wherein the image acquisition module includes a camera unit; the camera unit is used for acquiring the inspection image aiming at the fan.
6. The blower inspection robot of claim 1, wherein the artificial intelligence module processes the inspection image based on image recognition techniques to identify the type of fault present in the blower.
7. The blower inspection robot of claim 1, further comprising a sensing module;
the sensing module is used for acquiring communication parameters of the fan inspection robot.
8. The blower inspection robot according to any one of claims 1-7, wherein the first communication mode is near field wireless communication and the second communication mode is far field wireless communication.
9. A fan inspection system, comprising: a host computer, a patrol track and at least one fan patrol robot according to any one of claims 1 to 8;
the upper computer is used for controlling the fan inspection robot.
10. The blower inspection system of claim 9, wherein the upper computer comprises a cooperative control unit and a wireless communication unit;
the cooperative control unit is used for preparing control logic for executing the inspection task of each fan inspection robot and determining the inspection range of each fan inspection robot; the wireless communication unit is used for sending the control logic and the inspection range generated by the cooperative control unit to each fan inspection robot.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310523863.6A CN116778597A (en) | 2023-05-05 | 2023-05-05 | Fan inspection robot and fan inspection system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310523863.6A CN116778597A (en) | 2023-05-05 | 2023-05-05 | Fan inspection robot and fan inspection system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN116778597A true CN116778597A (en) | 2023-09-19 |
Family
ID=87985018
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202310523863.6A Pending CN116778597A (en) | 2023-05-05 | 2023-05-05 | Fan inspection robot and fan inspection system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116778597A (en) |
-
2023
- 2023-05-05 CN CN202310523863.6A patent/CN116778597A/en active Pending
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113112086B (en) | Intelligent production system based on edge calculation and identification analysis | |
CN110488841B (en) | Transformer equipment combined inspection system based on intelligent robot and application method thereof | |
CN112668237B (en) | Digital twin model based on industrial Internet cloud platform and construction method thereof | |
CN112085261B (en) | Enterprise production status diagnosis method based on cloud fusion and digital twin technology | |
CN111508097B (en) | Site inspection method, device, equipment and storage medium | |
CN104142663B (en) | Industrial equipment and system in cloud platform are proved | |
CN104616124A (en) | Real-time issuing method and system of safe and economic operation state of thermal power plant | |
KR101825881B1 (en) | Method of managing a manufacturing process and system using the same | |
CN109028481A (en) | Unattended machine room control system and method of air conditioning system | |
KR102097448B1 (en) | Distributed data acquisition and distributed control command system for factory automation, and Distributed data collection and distributed control method for the same | |
CN101937214A (en) | Industrial Ethernet based monitoring system of sea-crossing suspension bridge | |
CN116880396A (en) | Intelligent factory dynamic cooperative scheduling method | |
CN116628633A (en) | IGBT real-time monitoring and service life prediction evaluation method | |
CN113157679A (en) | Monitoring system and method of hydraulic generator set system | |
CN117389742B (en) | Edge computing method, device and storage medium for machine vision | |
CN111985352A (en) | AI front-end substation inspection video real-time identification method and system | |
CN114384881A (en) | Workshop logistics monitoring and simulation system and method based on digital twins | |
KR20190140508A (en) | System for managing power facilities | |
CN116778597A (en) | Fan inspection robot and fan inspection system | |
CN115092218B (en) | Full life cycle intelligent operation and maintenance system of high-speed railway signal system | |
CN116257006A (en) | Intelligent spot inspection system and method for electric equipment of cigarette factory | |
CN208759552U (en) | A kind of data center's intelligent robot | |
CN113172641A (en) | Movable intelligent robot based on multi-standard 5G module | |
KR101977540B1 (en) | Energy management system using drone in facility | |
US20200202178A1 (en) | Automatic visual data generation for object training and evaluation |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |