CN211718505U - Electric quantity instrument precision testing device based on neural network - Google Patents
Electric quantity instrument precision testing device based on neural network Download PDFInfo
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- CN211718505U CN211718505U CN201922468955.0U CN201922468955U CN211718505U CN 211718505 U CN211718505 U CN 211718505U CN 201922468955 U CN201922468955 U CN 201922468955U CN 211718505 U CN211718505 U CN 211718505U
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- instrument precision
- testing device
- precision testing
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Abstract
The utility model discloses an electric quantity instrument precision testing device based on a neural network, which comprises a main body and a control box, wherein a rotating motor is arranged above the main body, the end of the rotating motor is connected with a conveyor belt, one side of the conveyor belt is provided with a rotating steering engine, the end of the rotating steering engine is connected with a mechanical clamp, the end of the mechanical clamp is provided with a mechanical claw, the inner side of the mechanical claw is provided with an adsorption device, the front part of the mechanical clamp is provided with a detection table, an LCR tester is arranged above the detection table, one side of the main body is provided with the control box, the control box is provided with a control panel, the other side of the main body is provided with the control box, the more humanized clamping instrument is arranged on the conveyor belt for measurement, the tester is mainly used for testing inductance, capacitance and resistance, and, more accurate and precise precision of the measuring instrument.
Description
Technical Field
The utility model relates to a testing arrangement specifically is a power instrument precision testing arrangement based on neural network.
Background
With the development of science and technology and the improvement of living standard of people, various electric energy devices gradually enter the lives of people. With the rapid development of national economy, the demand for electric power is increasing day by day. In power supply and distribution systems, it is often necessary to detect a number of power parameters, such as voltage, current, power factor, harmonics, etc., in real time. In addition, the promotion of energy conservation and emission reduction puts forward the requirement of electric energy metering on energy utilization equipment or energy utilization areas. The current transformer is an important component of electric energy metering, and plays an important role in normal operation and accurate metering of electric energy metering. Therefore, in order to meet the metering requirements of the circuit breaker, the measurement accuracy of the current transformer must be improved.
In addition, the measuring device has a measuring frequency from industrial frequency to about 100 kilohertz. The basic measurement error is 0.02%, generally about 0.1%, various element parameters can be accurately and stably measured, but the current measuring device is not mature enough, the measuring mode is not intelligent enough, and the precision of an instrument device cannot be accurately measured, so improvement is needed.
Disclosure of Invention
The invention aims to provide a neural network-based electric quantity instrument precision testing device to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides an electric quantity instrument precision testing arrangement based on neural network, includes main part and control box, the main part top is provided with rotates the motor, it has the conveyer belt to rotate motor end-to-end connection, conveyer belt one side is provided with the rotation steering wheel, it has the mechanical clamp to rotate steering wheel end-to-end connection, the mechanical clamp end is provided with the gripper, the gripper inboard is provided with adsorption equipment, machinery presss from both sides the place ahead and is provided with detects the platform, it is provided with the LCR tester to detect the platform top, main part one side is provided with the control box, be provided with control panel on the control box, the main part opposite side is provided with.
Preferably, the conveying belt is fixedly connected to the main body through a fixing device, so that the conveying belt is convenient to detach and replace.
Preferably, the rotating motor is a brushless servo motor, so that the rotating speed is more conveniently controlled.
Preferably, a signal wire inside the alarm device is connected to a control panel inside the control box, so that the safety performance of the device is guaranteed.
Preferably, control panel includes display screen and control button, the display screen below is provided with a plurality of control button has realized more audio-visual control.
Preferably, the control panel in the control box is a raspberry pi 4B, the raspberry pi 4B is connected with the neural network computing rod, and deep learning is performed by adopting an artificial neural network method.
Compared with the prior art, the invention has the beneficial effects that: the utility model discloses a it is portable to set up the device, and the setting of conveyer belt is more humanized presss from both sides and gets the instrument and measure, is mainly the tester that is used for testing inductance, electric capacity, resistance. It has characteristics such as the function is direct, easy and simple to handle, can satisfy production line quality assurance, stock inspection, electron maintenance industry to the test requirement of device with lower budget, the utility model discloses an artificial intelligence's neural network carries out the degree of depth study, the precision of more accurate and accurate measuring instrument.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic view of the mechanical clamp of the present invention;
FIG. 3 is a schematic view of the control box of the present invention
In the figure: 1-a body; 2-rotating the steering engine; 3-mechanical clamping; 4-detecting the platform; 5-rotating the motor; 6-a control box; 7-a fixing device; 8-an alarm device; 9-a conveyor belt; 10-an adsorption device; 11-a gripper; 12-a control panel; 13-a display screen; 14-control keys; 15-LCR tester.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
Referring to fig. 1-3, the present invention provides a technical solution: the utility model provides an electric quantity instrument precision testing arrangement based on neural network, includes main part 1 and control box 6, 1 top in main part is provided with rotates motor 5, 5 end-to-end connection of rotation motor has conveyer belt 9, 9 one side of conveyer belt is provided with rotation steering wheel 2, 2 end-to-end connection of rotation steering wheel have mechanical clamp 3, 3 ends of mechanical clamp are provided with gripper 11, gripper 11 inboard is provided with adsorption equipment 10, 3 the place ahead that machinery pressed from both sides is provided with detects platform 4, it is provided with LCR tester 15 to detect 4 tops of platform, 1 one side in main part is provided with control box 6, be provided with control panel 12 on control box 6, 1 opposite side in main part is provided with alarm device 8.
The conveying belt 9 is fixedly connected to the main body 1 through the fixing device 7, and therefore the conveying belt is convenient to detach and replace. The rotating motor 5 is a brushless servo motor, and rotation speed control is more convenient to carry out. The signal wire in the alarm device 8 is connected with the control panel in the control box 6, so that the safety performance of the device is ensured. Control panel 12 includes display screen 13 and control button 14, display screen 13 below is provided with a plurality of control button 14 has realized more audio-visual control. The control panel inside the control box 6 is a raspberry pi 4B, the raspberry pi 4B is connected with a neural network computing rod, and deep learning is performed by adopting an artificial neural network method.
The working principle is as follows: the utility model discloses at first open the switch, then according to 12LCR testers 15 of control panel, adsorption equipment 10 in the mechanical clamp 3 can adsorb the instrument, 11 cooperations of gripper snatch, rotate steering wheel 5 and conveniently rotate the direction, alarm device 8 can report to the police, it can drive conveyer belt 9 and convey to rotate motor 5, then put and detect on the test table 4, voltage V and resistance r in the LCR testers 125 all are the vector voltmeter, Rr is ideal resistance. When the DUT is connected to the circuit, the negative feedback configuration of the amplifier automatically causes the OP input to be virtually grounded. V accurately measures the voltage at two ends of the DUT (the Low potential of the DUT is 0), R and Rr measure the current Ix of the DUT, Zx can be calculated, the measurement object of the digital bridge is the parameter of an impedance element, comprising an alternating current resistor R, an inductor L and a quality factor Q thereof, a capacitor C and a loss factor D thereof, and in addition, a neural network computing bar in the raspberry group can carry out deep learning, so that the identification precision is improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. The utility model provides an electric quantity instrument precision test device based on neural network which characterized in that: including main part (1) and control box (6), main part (1) top is provided with rotation motor (5), rotation motor (5) end-to-end connection has conveyer belt (9), conveyer belt (9) one side is provided with rotation steering wheel (2), rotation steering wheel (2) end-to-end connection has machinery to press from both sides (3), machinery presss from both sides (3) end and is provided with gripper (11), gripper (11) inboard is provided with adsorption equipment (10), machinery is pressed from both sides (3) the place ahead and is provided with and detects platform (4), it is provided with LCR tester (15) to detect platform (4) top, main part (1) one side is provided with control box (6), be provided with control panel (12) on control box (6), main part (1) opposite side is provided with alarm device (8).
2. The neural network-based coulometric instrument precision testing device of claim 1, wherein: the conveyor belt (9) is fixedly connected to the main body (1) through a fixing device (7).
3. The neural network-based coulometric instrument precision testing device of claim 1, wherein: the rotating motor (5) is a brushless servo motor.
4. The neural network-based coulometric instrument precision testing device of claim 1, wherein: and a signal wire inside the alarm device (8) is connected with a control panel inside the control box (6).
5. The neural network-based coulometric instrument precision testing device of claim 1, wherein: the control panel (12) comprises a display screen (13) and control keys (14), and a plurality of control keys (14) are arranged below the display screen (13).
6. The neural network-based coulometric instrument precision testing device of claim 1, wherein: the control panel inside the control box (6) is a raspberry pi 4B, and the raspberry pi 4B is connected with a neural network computing rod.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201922468955.0U CN211718505U (en) | 2019-12-31 | 2019-12-31 | Electric quantity instrument precision testing device based on neural network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201922468955.0U CN211718505U (en) | 2019-12-31 | 2019-12-31 | Electric quantity instrument precision testing device based on neural network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN211718505U true CN211718505U (en) | 2020-10-20 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201922468955.0U Expired - Fee Related CN211718505U (en) | 2019-12-31 | 2019-12-31 | Electric quantity instrument precision testing device based on neural network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN211718505U (en) |
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2019
- 2019-12-31 CN CN201922468955.0U patent/CN211718505U/en not_active Expired - Fee Related
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20201020 Termination date: 20211231 |