Location

La Jolla, CA

Start Date

1-1-1993 12:00 PM

Description

As and when aircraft aged, fatigue problems appeared and the necessity for detecting cracks in the lap joint parts became obvious. Numerous systems were then developed to follow up cracks appearance and growth in rivet holes. If most of the inspection used to be manual, it is now partially automated since AEROSPATIALE developed the System of Inspection Assisted by Microprocessor (SIAM) in which an EC probe slides on the rivet lines [1]. At present, our research is focused on the diagnosis, last phase of the inspection. In order to process the inspection data, to speed up the control, and to improve the detection performances, a neural network has been developed.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

12A

Chapter

Chapter 3: Interpretive Signal Processing and Image Analysis

Section

Neural Networks

Pages

797-802

DOI

10.1007/978-1-4615-2848-7_101

Language

en

File Format

application/pdf

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Jan 1st, 12:00 PM

Neural network for automating diagnosis in aircraft inspection

La Jolla, CA

As and when aircraft aged, fatigue problems appeared and the necessity for detecting cracks in the lap joint parts became obvious. Numerous systems were then developed to follow up cracks appearance and growth in rivet holes. If most of the inspection used to be manual, it is now partially automated since AEROSPATIALE developed the System of Inspection Assisted by Microprocessor (SIAM) in which an EC probe slides on the rivet lines [1]. At present, our research is focused on the diagnosis, last phase of the inspection. In order to process the inspection data, to speed up the control, and to improve the detection performances, a neural network has been developed.