Neural Network-Based Inverse Analysis for Defect Identification with Laser Ultrasonics

Automation is an important issue in industry, particularly in inspection of underground facilities. This paper describes experimental evaluation of intelligent system for automatically detecting faulty areas in a real sewer pipe system. The proposed system can detect various types of faults and be implemented in a real time system. Its detection performance is 100%, when the false positive rate is 34%. This ratio is acceptable for sewer inspection, and the reduction of time and cost is also realized.

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Experimental evaluation of intelligent fault detection system for inspection of sewer pipes

Ahrary

Ishikawa

Okada

2007

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Neural Network-Based Inverse Analysis for Defect Identification with Laser Ultrasonics

Cited by 1 publication

References 28 publications

Experimental evaluation of intelligent fault detection system for inspection of sewer pipes

Experimental evaluation of intelligent fault detection system for inspection of sewer pipes

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