Online detection robot control system based on neural network

A control system and neural network technology, applied in the field of online inspection robot control system, can solve the problems of inaccurate identification, insufficient inspection accuracy, and inability to classify non-destructive inspection technology, achieving a small and lightweight size, high inspection accuracy, and rich features. Effect

Pending Publication Date: 2022-03-01
SHENYANG POLYTECHNIC UNIV
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  • Abstract
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Problems solved by technology

[0004] The invention provides a neural network-based online detection robot control system, which aims to solve the problems that the existing nondestructive testing technology cannot classify the identified defects, and the detection accuracy is not enough to be accurately identified.

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  • Online detection robot control system based on neural network
  • Online detection robot control system based on neural network
  • Online detection robot control system based on neural network

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Embodiment Construction

[0054] The present invention is further described below in conjunction with accompanying drawing:

[0055] Such as figure 1 The flow chart of a neural network-based online detection robot control system is shown. This system includes two single-chip microcomputers, namely stm32F103ZET6 single-chip microcomputer and pyAI-K210 single-chip microcomputer. The stm32F103ZET6 includes 1. the minimum control system of stm32 single-chip microcomputer, 2. SRAM memory expansion, 3. USB communication serial port 1, 4. Ultrasonic sensor, 5 buzzers, 6. Stepping motor drive, 7. Startup mode setting interface, 8. Startup mode setting interface switch circuit, pyAI-K210 single chip microcomputer includes: 9. Minimum control System, 10. OV2460 camera, 11. LCD display, 12. Power module, 13. Wireless and 14. LED indicators and other parts

[0056] Such as figure 2 with 3 Shown is a neural network-based online detection robot control system, the lower computer includes stm32 single-chip minimu...

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Abstract

The invention relates to the field of industrial nondestructive testing, in particular to an online detection robot control system based on a neural network. The lower computer comprises an stm32 singlechip minimum control system, an SRAM (Static Random Access Memory) memory extension, a starting mode setting interface module, a USB (Universal Serial Bus) communication serial port I, an ultrasonic sensor, a buzzer, a switching circuit module, a serial port communication module and a stepping motor driver, and the upper computer adopts a pyAI-K210 singlechip and comprises a camera, an LED (Light Emitting Diode) indicator lamp, an LCD (Liquid Crystal Display), a minimum control system and the like. According to the method, the surface defects can be detected, the recognized defects can be classified, manual defect information processing is reduced, a basis is provided for repairing of various types of defects, and therefore extension of human vision is achieved, and manpower and material resources are reduced and saved.

Description

technical field [0001] The invention belongs to the field of industrial non-destructive testing, in particular to an online testing robot control system based on a neural network. Background technique [0002] With the development of the economy, the development of artificial intelligence is changing with each passing day, and the scope of application of machine vision and industrial robots is becoming more and more extensive. For non-destructive testing, new pipelines are full of many working environments or situations where artificial vision is difficult to meet the detection requirements. Online defect detection The emergence of robots has improved the working conditions, but for the past defect detection, it can only detect defects but cannot classify the identified defects, and the detection accuracy is not enough to accurately identify problems, which greatly reduces the detection efficiency and quality. In modern industrial inspection, how to design an online defect d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B19/042
CPCG05B19/0423G05B2219/25257Y02P80/40
Inventor 葛前刘斌任建何璐瑶杜兵杨井凡马浩宁张松许光达解社娟张琳琦刘训佶
Owner SHENYANG POLYTECHNIC UNIV
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