CN216647177U - Airborne terminal defect recognition device based on front-end AI chip - Google Patents
Airborne terminal defect recognition device based on front-end AI chip Download PDFInfo
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- CN216647177U CN216647177U CN202123301483.3U CN202123301483U CN216647177U CN 216647177 U CN216647177 U CN 216647177U CN 202123301483 U CN202123301483 U CN 202123301483U CN 216647177 U CN216647177 U CN 216647177U
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Abstract
The utility model discloses an airborne terminal defect recognition device based on a front-end AI chip, which comprises an unmanned aerial vehicle unit and a ground control unit matched with the unmanned aerial vehicle unit, wherein the unmanned aerial vehicle unit comprises a microprocessor, a positioning module, an electromagnetic radiation detection module, a shooting module, a first memory, a power module and a first wireless communication module, the output ends of the positioning module, the electromagnetic radiation detection module and the shooting module are in communication connection with the input end of the microprocessor, and the first memory is in two-way communication connection with the microprocessor. According to the utility model, the unmanned aerial vehicle unit is provided with the electromagnetic radiation detection module, the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when the high-voltage wire is electrified, the distance between the unmanned aerial vehicle and the high-voltage wire is controlled according to the intensity of the electromagnetic radiation detected by the electromagnetic radiation detection wood block, the safety distance between the unmanned aerial vehicle and the high-voltage wire is ensured, and the working safety of the airborne end defect recognition device is improved.
Description
Technical Field
The utility model relates to the technical field of unmanned aerial vehicles, in particular to an airborne terminal defect recognition device based on a front-end AI chip.
Background
Carry on machine and carry on the camera through unmanned aerial vehicle and take the photo to the object that needs were tourd, judge through discerning the photo, thereby it changes to judge the object of touring, the staff overhauls according to the result of carrying on machine and carrying end defect recognition device discernment, the patrol of the common power supply line of machine and carrying end defect recognition device, because bird nest is often set up to bird on the power supply line, it mixes conducting substance such as wire to build the thing in the bird nest, thereby cause the influence to the power supply line safety.
However, the airborne end defect recognition device of the existing power supply line is influenced by high-voltage wire electromagnetic waves in the actual use process, the unmanned aerial vehicle is unstable in communication and has interruption phenomenon, and the unmanned aerial vehicle needs to keep the distance between the unmanned aerial vehicle and the high-voltage wire in the control process, otherwise, the unmanned aerial vehicle collides with the high-voltage wire, and safety accidents occur.
SUMMERY OF THE UTILITY MODEL
In order to overcome the technical problems, the utility model aims to provide an airborne end defect recognition device based on a front-end AI chip.A unmanned aerial vehicle unit is provided with an electromagnetic radiation detection module, the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when a high-voltage wire is electrified, and the distance between the unmanned aerial vehicle and the high-voltage wire is controlled according to the intensity of the electromagnetic radiation detected by an electromagnetic radiation detection wood block, so that the safe distance between the unmanned aerial vehicle and a high-voltage wire is ensured, and the working safety of the airborne end defect recognition device is improved; through setting up defect early warning module in ground control unit's inside, according to the result of image recognition module discernment through defect early warning module, the picture that will have the defect shows and marks in display module to longitude, latitude and height when shooing the picture of defect show, make things convenient for maintainer to fix a position the fault point fast, improve high-tension line's maintenance efficiency, the practicality is strong.
The purpose of the utility model can be realized by the following technical scheme:
the airborne terminal defect recognition device based on the front-end AI chip comprises an unmanned aerial vehicle unit and a ground control unit matched with the unmanned aerial vehicle unit, wherein the unmanned aerial vehicle unit comprises a microprocessor, a positioning module, an electromagnetic radiation detection module, a shooting module, a first memory, a power module and a first wireless communication module;
the output ends of the positioning module, the electromagnetic radiation detection module and the shooting module are in communication connection with the input end of the microprocessor, the first memory is in bidirectional communication connection with the microprocessor, the output end of the microprocessor is in communication connection with the input end of the power module, and the microprocessor is in bidirectional communication connection with the first wireless communication module;
the ground control unit comprises a central control processor, a second memory, a defect early warning module, a control module, a second wireless communication module, an image recognition module and a display module, wherein the second memory is in bidirectional communication with the central processing unit, the second wireless communication module is in bidirectional communication with the central processing unit, the image recognition module is in bidirectional communication with the central processing unit, the output end of the control module is in communication connection with the input end of the central processing unit, the output end of the central processing unit is in communication connection with the input end of the display module, and the first wireless communication module is in communication connection with the second wireless communication module;
the positioning module is used for positioning the longitude, the latitude and the height of the unmanned aerial vehicle unit;
the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when the high-voltage wire is electrified;
the power module is used for providing moving power for the unmanned aerial vehicle unit;
the shooting module is used for shooting pictures of the inspection objects of the unmanned aerial vehicle unit inspection path;
the control module is used for controlling the power module to move according to a specified direction;
the image identification module is used for identifying the picture shot by the unmanned aerial vehicle unit and feeding back the identification result to the central processing unit;
the display module is used for displaying pictures shot by the unmanned aerial vehicle unit;
and the defect early warning module is used for displaying and marking the pictures with defects in the display module according to the recognition result of the image recognition module.
Further, the method comprises the following steps: and the result output by the defect early warning module also comprises longitude, latitude and height information when the picture of the defect is shot.
Further, the method comprises the following steps: the first wireless communication module and the second wireless communication module are 4G/5G communication modules.
Further, the method comprises the following steps: the display module also displays the electromagnetic radiation intensity of the electromagnetic radiation detection module.
Further, the method comprises the following steps: the shooting module is a double-camera.
Further, the method comprises the following steps: the positioning module is a Beidou positioning module.
The utility model has the beneficial effects that:
1. the unmanned aerial vehicle unit is provided with the electromagnetic radiation detection module, the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when the high-voltage wire is electrified, then the distance between the unmanned aerial vehicle and the high-voltage wire is controlled according to the intensity of the electromagnetic radiation detected by the electromagnetic radiation detection wood block, the safety distance between the unmanned aerial vehicle and the high-voltage wire is ensured, and thus the collision between the unmanned aerial vehicle and the high-voltage wire can be avoided, and the working safety of the airborne end defect recognition device is improved;
2. through setting up defect early warning module in ground control unit's inside, according to the result of image recognition module discernment through defect early warning module, the picture that will have the defect shows and marks in display module to longitude, latitude and height when shooing the picture of defect show, make things convenient for maintainer to fix a position the fault point fast, improve high-tension line's maintenance efficiency, the practicality is strong.
Drawings
The utility model is further described below with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the onboard end defect recognition device based on a front end AI chip;
fig. 2 is a circuit diagram of an electromagnetic radiation detection module of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the airborne terminal defect recognition apparatus based on the front-end AI chip includes an unmanned aerial vehicle unit and a ground control unit matched with the unmanned aerial vehicle unit, wherein the unmanned aerial vehicle unit includes a microprocessor, a positioning module, an electromagnetic radiation detection module, a shooting module, a first memory, a power module and a first wireless communication module;
the output ends of the positioning module, the electromagnetic radiation detection module and the shooting module are in communication connection with the input end of the microprocessor, the first memory is in bidirectional communication connection with the microprocessor, the output end of the microprocessor is in communication connection with the input end of the power module, and the microprocessor is in bidirectional communication connection with the first wireless communication module;
the ground control unit comprises a central control processor, a second memory, a defect early warning module, a control module, a second wireless communication module, an image recognition module and a display module, wherein the second memory is in bidirectional communication connection with the central processing unit;
the positioning module is used for positioning the longitude, the latitude and the height of the unmanned aerial vehicle unit;
the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when the high-voltage wire is electrified;
the power module is used for providing moving power for the unmanned aerial vehicle unit;
the shooting module is used for shooting pictures of the inspection objects of the unmanned aerial vehicle unit inspection path;
the control module is used for controlling the power module to move according to a specified direction;
the image identification module is used for identifying the picture shot by the unmanned aerial vehicle unit and feeding back the identification result to the central processing unit;
the display module is used for displaying pictures shot by the unmanned aerial vehicle unit;
and the defect early warning module is used for displaying and marking the pictures with defects in the display module according to the recognition result of the image recognition module.
The result output by the defect early warning module also comprises longitude, latitude and height information when the picture of the defect is shot, and by marking the longitude, latitude and height information, a maintainer can conveniently judge a fault point according to the longitude and latitude and judge the height position of the fault point according to the height information.
First wireless communication module and second wireless communication module are 4G 5G communication module, and it is fast through 4G 5G communication module transmission rate, can realize long distance communication and connect, and display module still shows electromagnetic radiation detection module's electromagnetic radiation intensity, through showing electromagnetic radiation intensity, makes things convenient for operating personnel directly perceived to know the security level between unmanned aerial vehicle unit and the high-voltage wire.
The shooting module can realize the adjustment of different focuses for two cameras through two cameras, and the hierarchy nature of shooting is high, and orientation module is big dipper orientation module.
The sensing element used by the electromagnetic radiation detection module is an inductance coil L1 connected with a field effect transistor T1, a fixed resistor R1 and a variable resistor Aj1 which are connected in series are polarized at the beginning end of a conductive area of the T1, an amplified electromotive force generated in the L1 is presented on a drain electrode of a T1, an amplified signal presented on a terminal pin of the resistor R2 is sent to a second amplification stage arranged on a common emitter electrode established around an NPN transistor T2 through a capacitor C1, the amplitude of a signal presented on a collector electrode of the T2 depends on the intensity of peripheral radiation, a bias voltage is established on a base electrode of the T3 through the fixed resistors R5 and R6 and the variable resistor Aj2, and the voltage change is detected through a voltage U1 to realize the detection of the intensity of the electromagnetic wave.
The working principle is as follows: when in use, the power module of the unmanned aerial vehicle is controlled by the control module of the ground control unit to drive the unmanned aerial vehicle unit to move, then an operator controls the unmanned aerial vehicle unit to move to the position near a high-voltage line to be detected, the unmanned aerial vehicle unit detects the intensity of electromagnetic waves released by the high-voltage wire through an electromagnetic radiation detection module in the unmanned aerial vehicle unit, adjust the distance between unmanned aerial vehicle unit and the high-voltage wire according to electromagnetic wave intensity, shoot the photo along the line of high-voltage wire through shooting the module, the photo of shooting is transmitted to ground control unit through wireless communication module, ground control unit passes through the photo that image recognition module detected to have the defect, the photo that defect early warning module will have the defect shows, the staff arrives the defect place according to the picture that defect early warning module provided and the longitude and latitude of shooting the position, judge the defect point position according to height data, thereby carry out the quick maintenance.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the utility model. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is illustrative and explanatory only and is not intended to be exhaustive or to limit the utility model to the precise embodiments described, and various modifications, additions, and substitutions may be made by those skilled in the art without departing from the scope of the utility model as defined in the following claims.
Claims (6)
1. The airborne terminal defect recognition device based on the front-end AI chip is characterized by comprising an unmanned aerial vehicle unit and a ground control unit matched with the unmanned aerial vehicle unit, wherein the unmanned aerial vehicle unit comprises a microprocessor, a positioning module, an electromagnetic radiation detection module, a shooting module, a first memory, a power module and a first wireless communication module;
the output ends of the positioning module, the electromagnetic radiation detection module and the shooting module are in communication connection with the input end of the microprocessor, the first memory is in bidirectional communication connection with the microprocessor, the output end of the microprocessor is in communication connection with the input end of the power module, and the microprocessor is in bidirectional communication connection with the first wireless communication module;
the ground control unit comprises a central control processor, a second memory, a defect early warning module, a control module, a second wireless communication module, an image recognition module and a display module, wherein the second memory is in bidirectional communication connection with the central processing unit;
the positioning module is used for positioning the longitude, the latitude and the height of the unmanned aerial vehicle unit;
the electromagnetic radiation detection module is used for detecting the intensity of electromagnetic waves generated when the high-voltage wire is electrified;
the power module is used for providing moving power for the unmanned aerial vehicle unit;
the shooting module is used for shooting pictures of the inspection objects of the unmanned aerial vehicle unit inspection path;
the control module is used for controlling the power module to move according to a specified direction;
the image identification module is used for identifying the picture shot by the unmanned aerial vehicle unit and feeding back the identification result to the central processing unit;
the display module is used for displaying pictures shot by the unmanned aerial vehicle unit;
and the defect early warning module is used for displaying and marking the pictures with defects in the display module according to the recognition result of the image recognition module.
2. The device for recognizing the defect at the airborne terminal based on the front-end AI chip as claimed in claim 1, wherein the result outputted by the defect pre-warning module further comprises longitude, latitude and altitude information of the defect when the picture of the defect is taken.
3. The device of claim 1, wherein the first wireless communication module and the second wireless communication module are 4G/5G communication modules.
4. The front-end AI chip based on onboard terminal defect recognition device of claim 1, wherein the display module further displays the electromagnetic radiation intensity of the electromagnetic radiation detection module.
5. The front-end AI chip-based airborne end defect recognition device of claim 1, wherein the camera module is a dual camera.
6. The front-end AI chip-based airborne end defect recognition device of claim 1, wherein said positioning module is a Beidou positioning module.
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| CN202123301483.3U CN216647177U (en) | 2021-12-23 | 2021-12-23 | Airborne terminal defect recognition device based on front-end AI chip |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117557556A (en) * | 2024-01-09 | 2024-02-13 | 南京市特种设备安全监督检验研究院 | Intelligent detection method for defects of lifting equipment |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117557556A (en) * | 2024-01-09 | 2024-02-13 | 南京市特种设备安全监督检验研究院 | Intelligent detection method for defects of lifting equipment |
| CN117557556B (en) * | 2024-01-09 | 2024-03-26 | 南京市特种设备安全监督检验研究院 | Intelligent detection method for defects of lifting equipment |
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