CN115247742A - Deep learning computer state monitor - Google Patents
Deep learning computer state monitor Download PDFInfo
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- CN115247742A CN115247742A CN202210009104.3A CN202210009104A CN115247742A CN 115247742 A CN115247742 A CN 115247742A CN 202210009104 A CN202210009104 A CN 202210009104A CN 115247742 A CN115247742 A CN 115247742A
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- 238000013135 deep learning Methods 0.000 title claims abstract description 19
- 238000012423 maintenance Methods 0.000 claims abstract description 38
- 230000003068 static effect Effects 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 description 3
- 230000032683 aging Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16M—FRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
- F16M11/00—Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
- F16M11/42—Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters with arrangement for propelling the support stands on wheels
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16M—FRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
- F16M11/00—Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
- F16M11/02—Heads
- F16M11/04—Means for attachment of apparatus; Means allowing adjustment of the apparatus relatively to the stand
- F16M11/06—Means for attachment of apparatus; Means allowing adjustment of the apparatus relatively to the stand allowing pivoting
- F16M11/12—Means for attachment of apparatus; Means allowing adjustment of the apparatus relatively to the stand allowing pivoting in more than one direction
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
- F16M—FRAMES, CASINGS OR BEDS OF ENGINES, MACHINES OR APPARATUS, NOT SPECIFIC TO ENGINES, MACHINES OR APPARATUS PROVIDED FOR ELSEWHERE; STANDS; SUPPORTS
- F16M11/00—Stands or trestles as supports for apparatus or articles placed thereon ; Stands for scientific apparatus such as gravitational force meters
- F16M11/02—Heads
- F16M11/18—Heads with mechanism for moving the apparatus relatively to the stand
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
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- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Library & Information Science (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Controls And Circuits For Display Device (AREA)
Abstract
The invention discloses a deep learning computer state monitor, which receives a computer screen video shot by a camera, acquires information in a video picture when the video picture is static, searches a corresponding maintenance video according to the information in the video picture, and plays the maintenance video through a displayer; the universal rotator is also used for detecting that the size of a computer screen in a video picture is complete, and when the size of the computer screen is incomplete, the universal rotator is controlled to rotate so that the camera rotates until the size of the computer screen is complete. According to the invention, the display image of the computer screen is acquired through the video collector, when the computer has a problem, the fault reason of the computer is acquired by extracting the information on the display image, the corresponding self-service maintenance video is searched according to the fault reason of the computer, and finally, the user is guided to carry out self-service maintenance on the computer in a video playing mode.
Description
Technical Field
The invention relates to the field of computer equipment, in particular to a deep learning computer state monitor.
Background
The development and use of computers make people's life more convenient and faster, but most people are limited to how to use computers, and the principle and structure of the computers are unclear, so when people use computers, the computers often fail due to aging of machines or misoperation, and the computers are in a state of being incapable of being used normally.
Disclosure of Invention
The invention aims to overcome the problems in the prior art and provide a deep learning computer state monitor, wherein a video collector is used for collecting a display image of a computer screen, and when the computer has a problem, a user is guided to carry out autonomous maintenance on the computer in a video playing mode.
To this end, the present invention provides a deep learning computer state monitor comprising: a base; the display is arranged on the base, and the top of the display is connected with a camera through a universal rotator; the processor is used for receiving the computer screen video shot by the camera, acquiring information in the video picture when the video picture is static, searching a corresponding maintenance video according to the information in the video picture, and playing the maintenance video through the displayer; the universal rotator is also used for detecting that the size of a computer screen in a video picture is complete, and when the size of the computer screen is incomplete, the universal rotator is controlled to rotate so that the camera rotates until the size of the computer screen is complete; and the power supply is used for supplying power to the processor, the universal rotator, the displayer and the camera.
Furthermore, a universal driving wheel is arranged at the bottom of the base, a plurality of accommodating grooves are respectively formed in the bottom of the base along the circumferential direction of the base, a ball is respectively arranged in each accommodating groove, and the bottoms of the balls and the bottom of the universal driving wheel are located on the same plane; when the processor controls the universal rotator to rotate and the size of the computer screen is still incomplete within a set time, the processor controls the universal driving wheel until the size of the computer screen is complete; the power supply is also used for supplying power to the universal driving wheel.
Furthermore, the processor detects the size of the computer screen by detecting the integrity of the frame of the computer screen when detecting the integrity of the size of the computer screen, and detects the size of the computer screen by detecting the image recognition technology when detecting the integrity of the frame of the computer screen.
Furthermore, when the processor controls the rotating direction of the universal rotator, the processor establishes a direction vector by detecting the position of a computer screen in the video picture, taking the center of the video picture as an original point and the center of the computer screen as an end point, and controls the rotating direction of the universal rotator according to the direction vector.
Furthermore, when the processor controls the movement direction of the universal driving wheel, the processor establishes a direction vector by detecting the position of a computer screen in the video picture, taking the center of the video picture as an original point and the center of the computer screen as an end point, and controls the movement direction of the universal driving wheel according to the direction vector.
Further, the display is a 3D projector.
Furthermore, the processor is further configured to detect a maintenance status of the user, and when the user is in the maintenance status, the processor controls the projection of the display to be directed to the user.
Furthermore, the processor is also used for detecting the difference between the maintenance state of the user and the maintenance video, and displaying the difference part to the user by using the displayer in a highlighting mode.
The deep learning computer state monitor provided by the invention has the following beneficial effects:
1. the method comprises the steps that a video collector collects a display image of a computer screen, when a computer has a problem, the fault reason of the computer is obtained by extracting information on the display image, a corresponding self-service maintenance video is searched according to the fault reason of the computer, and finally a user is guided to carry out self-service maintenance on the computer in a video playing mode;
2. when the video playing system is used for playing, the 3D projection device is used for projecting the maintained video onto the computer, so that a user can maintain the computer according to the difference between the user and the 3D projection, and meanwhile, the action of the user is detected and the behavior of the user is guided in a highlight display mode.
Drawings
FIG. 1 is a schematic cross-sectional view of the overall structure of the present invention;
FIG. 2 is a diagram illustrating data transfer relationships according to the present invention;
FIG. 3 is a fragmentary view of the size of a computer screen in a video frame;
fig. 4 is a full schematic view of the size of a computer screen in a video frame.
Description of reference numerals:
1. a camera; 2. a universal rotator; 3, accommodating grooves; 4. a universal driving wheel; 5. a ball bearing; 6. a base; 7. a display.
Detailed Description
Several embodiments of the present invention will be described in detail below with reference to the drawings, but it should be understood that the scope of the present invention is not limited to the embodiments.
In the present application, the type and structure of components that are not specified are all the prior art that is well known to those skilled in the art, and those skilled in the art can set the components according to the needs of the actual situation, and the embodiments in the present application are not specifically limited.
Specifically, as shown in fig. 1-4, an embodiment of the present invention provides a deep learning computer state monitor, including: a base 6, a display 7, a processor, and a power source. Wherein, the base 6 is used for supporting the product of the invention; the display 7 is arranged on the base 6, the top of the display is connected with the camera 1 through the universal rotator 2, and the camera 1 is aligned with a computer screen and used for shooting the computer screen; the processor is used for receiving the computer screen video shot by the camera 1, acquiring information in the video picture when the video picture is static, searching a corresponding maintenance video according to the information in the video picture, and playing the maintenance video through the displayer 7; the universal rotator is also used for detecting that the size of a computer screen in a video picture is complete, and when the size of the computer screen is incomplete, the universal rotator 2 is controlled to rotate so that the camera 1 rotates until the size of the computer screen is complete; the power supply is used for supplying power to the processor, the universal rotator 2, the displayer 7 and the camera 1.
When a user uses the product provided by the invention, the product is placed on the desktop of a computer desk or other places, so that the camera 1 can face a computer screen display, the computer screen can work well, the screen can be directly embodied when the computer has a fault by monitoring the computer screen, the fault embodied by the computer screen is acquired by using a deep learning mode, then a maintenance mode for repairing the fault is obtained, and the maintenance mode is displayed to the user in a video mode, so that the user can quickly maintain the computer.
The invention can effectively judge the computer fault by integrally detecting the condition of the computer screen and combining with the deep learning, for example, the computer screen is still for a long time and can be regarded as the computer crash, or the computer screen blue screen can obtain the computer fault by identifying the characters on the blue screen which are suitable for the computer, and the computer fault can be obtained in a deep learning way in a processor.
In the embodiment of the present invention, a universal driving wheel 4 is disposed at the bottom of the base 1, a plurality of accommodating grooves 3 are respectively disposed at the bottom of the base 1 along the circumferential direction thereof, a ball 5 is respectively disposed in each accommodating groove 3, and the bottom of each ball 5 and the bottom of the universal driving wheel 4 are located on the same plane; when the processor controls the universal rotator 2 to rotate and the size of the computer screen is still incomplete within a set time, the processor controls the universal driving wheel 4 until the size of the computer screen is complete; the power supply is also used to supply power to the universal drive wheel 4.
The universal driving wheel 4 is used for adjusting the position of the invention, the ball 5 moves to match the movement of the universal driving wheel 4 and is used for supporting the base 1, the universal driving wheel 4 is used for reducing the requirement of a user on the placement position on a table, and the content of the video to be shot by the invention is complete through an automatic adjustment mode.
Meanwhile, as an optimal technical scheme of the embodiment, when the processor detects that the size of the computer screen is complete, the processor detects the computer screen by detecting that the frame of the computer screen is complete, and when the frame of the computer screen is detected to be complete, the processor detects the computer screen by using an image recognition technology. By only detecting the frame, the workload of operation can be effectively reduced, so that the system operation speed of the product is increased, and the product can be quickly positioned and find out a proper position and angle when in use.
Meanwhile, for the adjustment of the angle, as a preferred technical solution of this embodiment, when controlling the rotation direction of the universal rotator 2, the processor establishes a direction vector by detecting the position of the computer screen in the video picture, taking the center of the video picture as an origin, taking the center of the computer screen as an end point, and controls the rotation direction of the universal rotator 2 according to the direction vector.
Meanwhile, for the adjustment of the position, as a preferred technical solution of this embodiment, when controlling the direction of the movement of the universal driving wheel 4, the processor establishes a direction vector by detecting the position of the computer screen in the video picture, taking the center of the video picture as an origin and the center of the computer screen as an end point, and controls the direction of the movement of the universal driving wheel 4 according to the direction vector.
Therefore, the position and the direction angle of the camera are adjusted from the two aspects of position and angle, so that the picture shot by the camera 1 comprises a complete computer display, and the requirement of a user on position limitation in use is reduced.
In an embodiment of the invention, the display 7 is a 3D projector. Through the 3D mode, a user can see details more easily when the user performs maintenance in comparison with a video, the maintenance mode and the maintenance method are accurate, the method is suitable for users who do not know the computer, the computer can be effectively prevented from being damaged by the user during maintenance, the trial and error times of invalid maintenance can be reduced when the user performs maintenance, and the user can perform maintenance in place once.
Meanwhile, as a preferred technical solution of this embodiment, the processor is further configured to detect a maintenance state of the user, and when the user is in the maintenance state, the processor controls the projection of the display 7 to be directed to the user. When the projection of the presenter 7 is directed to the user, the 3D projection can be mapped onto the machine the user is servicing, so that the display is at the user's eye, and the user can contrast the servicing according to the frontal projection, so that at the time of servicing, there is no need to look at the product of the invention in large amounts.
Meanwhile, as a preferred technical solution of this embodiment, the processor is further configured to detect a difference between the maintenance state of the user and the maintenance video, and display the difference portion to the user by using the display 7 in a highlight display manner. The invention displays the difference part to the user, so that the user can know the difference between the self maintenance and the correct maintenance, and the correct maintenance mode can be better contrasted, thereby ensuring that the computer is more accurate and rapid in maintenance and is rapidly separated from the fault.
The above disclosure is only for a few specific embodiments of the present invention, however, the present invention is not limited to the above embodiments, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present invention.
Claims (8)
1. A deep learning computer state monitor, comprising:
a base (6);
the display (7) is arranged on the base (6), and the top of the display is connected with the camera (1) through the universal rotator (2);
the processor is used for receiving the computer screen video shot by the camera (1), acquiring information in the video picture when the video picture is static, searching a corresponding maintenance video according to the information in the video picture, and playing the maintenance video through the displayer (7); the camera is also used for detecting the size completeness of a computer screen in a video picture, and when the size of the computer screen is incomplete, the universal rotator (2) is controlled to rotate so that the camera (1) rotates until the size of the computer screen is complete;
and the power supply is used for supplying power to the processor, the universal rotator (2), the displayer (7) and the camera (1).
2. A deep learning computer status monitor as claimed in claim 1, wherein the bottom of the base (1) is provided with a universal driving wheel (4), the bottom of the base (1) is provided with a plurality of receiving grooves (3) along the circumference thereof, each receiving groove (3) is provided with a ball (5), the bottom of the ball (5) and the bottom of the universal driving wheel (4) are located on the same plane;
when the processor controls the universal rotator (2) to rotate and the size of the computer screen is still incomplete within a set time, the processor controls the universal driving wheel (4) until the size of the computer screen is complete;
the power supply is also used for supplying power to the universal driving wheel (4).
3. The deep learning computer state monitor of claim 2, wherein the processor detects the computer screen by detecting that its dimensions are complete and by detecting that its borders are complete and by image recognition.
4. A deep learning computer state monitor as claimed in claim 3, wherein the processor, when controlling the direction of rotation of the universal rotator (2), establishes a direction vector by detecting the position of the computer screen in the video picture, with the center of the video picture as the origin and the center of the computer screen as the end point, and controls the direction of rotation of the universal rotator (2) according to the direction vector.
5. A deep learning computer state monitor as claimed in claim 3, wherein the processor, when controlling the direction of movement of the universal drive wheel (4), establishes a direction vector by detecting the position of the computer screen in the video frame, with the centre of the video frame as the origin and the centre of the computer screen as the destination, and controls the direction of movement of the universal drive wheel (4) in dependence on the direction vector.
6. A deep learning computer state monitor according to claim 1, characterized in that the display (7) is a 3D projector.
7. A deep-learning computer state monitor according to claim 6, characterized in that the processor is further adapted to detect a maintenance state of the user, the processor controlling the projection of the display (7) to be directed to the user when the user is in the maintenance state.
8. The deep learning computer status monitor as claimed in claim 7, wherein the processor is further configured to detect a difference between a maintenance status of the user and a maintenance video, and to display the difference portion to the user using the display (7) by highlighting.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210009104.3A CN115247742A (en) | 2022-01-05 | 2022-01-05 | Deep learning computer state monitor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210009104.3A CN115247742A (en) | 2022-01-05 | 2022-01-05 | Deep learning computer state monitor |
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| CN115247742A true CN115247742A (en) | 2022-10-28 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202210009104.3A Pending CN115247742A (en) | 2022-01-05 | 2022-01-05 | Deep learning computer state monitor |
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Citations (7)
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| JP2008217545A (en) * | 2007-03-06 | 2008-09-18 | Nec Corp | Console information acquisition system, console information acquisition method, and console information acquisition program |
| CN202013569U (en) * | 2011-03-16 | 2011-10-19 | 中冶建工有限公司 | Self-service analyzer for fault of computer |
| CN102857361A (en) * | 2011-07-02 | 2013-01-02 | 杨源杰 | Light-weight remote computer out-of-band management method |
| CN106383763A (en) * | 2016-05-30 | 2017-02-08 | 徐克� | Data center intelligent fault detection alarm system |
| CN106851057A (en) * | 2016-11-08 | 2017-06-13 | 国网浙江省电力公司湖州供电公司 | It is a kind of by program error it is encoded translated be the system of error description |
| CN110413489A (en) * | 2019-07-31 | 2019-11-05 | 浪潮商用机器有限公司 | Quickly system, method, equipment and the storage medium of identification server failure code |
| CN110738336A (en) * | 2019-10-23 | 2020-01-31 | 江苏世丰知识产权管理咨询有限公司 | office computer timely maintenance management system |
-
2022
- 2022-01-05 CN CN202210009104.3A patent/CN115247742A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008217545A (en) * | 2007-03-06 | 2008-09-18 | Nec Corp | Console information acquisition system, console information acquisition method, and console information acquisition program |
| CN202013569U (en) * | 2011-03-16 | 2011-10-19 | 中冶建工有限公司 | Self-service analyzer for fault of computer |
| CN102857361A (en) * | 2011-07-02 | 2013-01-02 | 杨源杰 | Light-weight remote computer out-of-band management method |
| CN106383763A (en) * | 2016-05-30 | 2017-02-08 | 徐克� | Data center intelligent fault detection alarm system |
| CN106851057A (en) * | 2016-11-08 | 2017-06-13 | 国网浙江省电力公司湖州供电公司 | It is a kind of by program error it is encoded translated be the system of error description |
| CN110413489A (en) * | 2019-07-31 | 2019-11-05 | 浪潮商用机器有限公司 | Quickly system, method, equipment and the storage medium of identification server failure code |
| CN110738336A (en) * | 2019-10-23 | 2020-01-31 | 江苏世丰知识产权管理咨询有限公司 | office computer timely maintenance management system |
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