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Blade detection method and system based on machine vision

A technology of machine vision and detection method, applied in the fields of aerospace and ships, can solve problems such as low efficiency of manual detection, and achieve the effect of solving low efficiency of manual detection

Pending Publication Date: 2021-11-30
CHONGQING UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a blade detection method and system based on machine vision, aiming to solve the technical problem of low efficiency of manual detection of turbine blade fluorescence penetration detection in the prior art

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  • Blade detection method and system based on machine vision
  • Blade detection method and system based on machine vision
  • Blade detection method and system based on machine vision

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Embodiment Construction

[0032] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0033] see Figure 1 to Figure 5 , the present invention proposes a blade detection system based on machine vision, including a loading and unloading classification mechanism 1, an optical detection device 2, a device casing 3 and an upper computer operating device 4, and the device casing 3 is an inner hollow cavity, so The loading and unloading classification mechanism 1 and the optical detection device 2 are respectively arranged in the device casing 3, and the host computer operating device 4 is movably connected with the dev...

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Abstract

The invention discloses a blade detection method and system based on machine vision. After fluorescent permeation is carried out on a cast blade, the process operations of clamping, transferring, adjusting, overturning, classifying and the like of the blade are realized through a feeding and discharging classification mechanism, and the identity code of the blade is automatically acquired and identified; in addition, fluorescent permeation defect data of the surface of the blade is collected in an ultraviolet light environment, a deep learning algorithm is adopted, model training is completed according to an image sample, finally, intelligent scoring and defect level judgment are carried out, and defective blades of different levels are sorted into a charging barrel, so that high-automation integration is realized, and the technical problem that the manual detection efficiency of turbine blade fluorescent permeation detection in the prior art is low is solved.

Description

technical field [0001] The invention relates to the technical fields of aerospace and shipbuilding, in particular to a machine vision-based blade detection method and system. Background technique [0002] Turbine blades are the core components of marine gas turbines. They are used in harsh environments and need to withstand high temperature and high pressure gas and cycle alternating loads and centrifugal loads. Due to the complex shape of the blade and the high casting defect rate, there are many factors affecting its structure and performance, such as the complexity of the alloy composition, unreasonable process conditions and parameters, etc., which can cause defects such as inclusions, porosity, pores and cracks. Significant impact on engine service life and reliability. Artificial fluorescence penetrant testing is the most important non-destructive testing method to ensure the surface quality of alloy castings. It can detect defects such as cracks, inclusions, and poro...

Claims

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Application Information

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IPC IPC(8): B07C5/34B07C5/02B07C5/38G01N21/91G01N21/64G01N21/01
CPCB07C5/34B07C5/02B07C5/38G01N21/91G01N21/6428G01N21/01G01N2021/6439G01N2021/0112
Inventor 刘飞刘海清王月蔡小雨王鹏
Owner CHONGQING UNIV OF POSTS & TELECOMM