Automated Surface Failure Classification for Aircraft Component Repair
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Solution Overview
Problem
Current methods for inspecting and repairing surface failures on aircraft and car components, such as metal and resin members, rely on manual visual inspection and marking, leading to inefficient processing due to varying failure shapes requiring different repair methods, like filling recessed areas or removing protrusions.
Innovation Solution
A member inspection device with an irradiation device, image pickup device, failure detection device, and determining device classifies failure shapes, allowing for targeted repair material application and marking, optimizing the repair process based on detected shapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If only marking is carried out on the processed portion in which a process is required, then the inspection work can be automated, but the worker needs to check the shape of the marked processed portion and select a repairing work, which creates a problem of poor working efficiency
Solution Approach 1:
The determining device performs preliminary classification of failure shapes (recessed portion, protrusion portion, or neither) before the repair process. This preliminary action provides the worker with pre-analyzed information about the failure type, eliminating the need for manual shape assessment and enabling more efficient repair work selection.
Solution Approach 2:
The determining device acts as an intermediary between the inspection robot and the worker. It processes the detected failure information and classifies the failure shape, then provides this classified information to the worker. This intermediary function bridges the gap between automated detection and manual repair decision-making, improving overall workflow efficiency.
2Measurement precision
If manual visual inspection is carried out by a worker on a number of members individually, then the worker can check the coated surfaces, but the inspection work is heavy labor, puts a heavy burden on the worker, and extends work hours, which deteriorates the working efficiency
Solution Approach 1:
The inspection robot with imaging equipment replaces the manual visual inspection performed by the worker. The robot automatically captures images of the coated surfaces and the determining device classifies failure shapes, substituting the mechanical visual inspection process with an automated optical system. This eliminates heavy labor and extends working hours while maintaining inspection quality.
Solution Approach 2:
The inspection system performs self-service by automatically detecting and classifying failures without requiring continuous human intervention. The robot autonomously moves along the conveyance line, captures images, and the determining device automatically analyzes the failure shapes, making the inspection process self-sufficient and highly efficient.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The device improves working efficiency by automating the detection and classification of failure shapes, enabling precise and efficient repair treatments, reducing manual labor and extending the inspection and repair process efficiency.
Implementation Method 1
an irradiation device that irradiates a surface to be inspected of a member with light
Implementation Method 2
an image pickup device that picks up an image of an irradiated portion of the light on the surface to be inspected
Data Source
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AI summary
The present invention is provided with, in a member inspection device and a member repairing method: an irradiation device (11) that irradiates a surface (101) of a member (100) with light, said surface being to be inspected; an image pickup device (12) that picks up an image of a surface (101) portion irradiated with the light; a failure detection device (13) that detects a failure area on the basis of a photographed image picked up by means of the image pickup device (12); and a determining device (14) that classifies the shape of the failure area detected by means of the failure detection device (13).