A NEURAL NETWORK MODEL FOR ULTRASONIC FLAW SIZING
Source abstract
Abstract
Abstract A multilayered neural network model is used here for solving an inverse sizing problem in the field of ultrasonic nondestructive evaluation. In particular, a feed-forward network trained via the error backpropagation algorithm is shown to be able to invert size and orientation information for circular cracks from time domain ultrasonic data. Test results of the network's performance on both theoretical and experimental data are presented. A new adaptive learning scheme for improving the training speed of such methods is also presented.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Machine Fault Diagnosis Techniques · Advanced machining processes and optimization · Metallurgy and Material Forming
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (24)
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