A NEURAL NETWORK FOR DEPTH DETERMINATION OF SEPARATIONS BETWEEN A RUBBER MATRIX AND REINFORCING STEEL BELTS

机译：神经网络，用于橡胶基质和钢筋带之间深度的确定

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A neural network for depth determination of separations between a rubber matrix and reinforcing steel belts has been developed. To evaluate a separation depth up to 10 mm, the neural network has been designed and constructed of four sub-neural networks. Each sub-network has been trained by using simulated time-domain signals reflected by the structure containing separations at various depths. A classifier that employs a cross-correlation algorithm and a gate are used to preprocess input data and to send the signal to the desired sub-network. The neural network has been tested on both simulated and measured signals. The estimated depths of separations agree well with the actual ones.

机译：已经开发了用于深度确定橡胶基体和增强钢带之间分离的神经网络。为了评估最大10 mm的分离深度，神经网络已设计并由四个亚神经网络构成。通过使用模拟时域信号对每个子网进行训练，该模拟时域信号由包含不同深度间隔的结构反射。使用互相关算法和门的分类器可用于预处理输入数据，并将信号发送到所需的子网。神经网络已经在模拟和测量信号上进行了测试。估计的分离深度与实际深度非常吻合。

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来源
《Annual Symposium on Quantitative Nondestructive Evaluation; 19980719-24; Snowbird,UT(US)》|1998年|P.835-841|共7页
会议地点 SnowbirdUT(US)
作者
A. P. Cheng; A. Cheng; R. Rogers; J. D. Achenbach;
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Center for Quality Engineering and Failure Prevention Northwestern University, Evanston, IL 60208-3020;

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正文语种 eng
中图分类无损探伤仪器;
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A NEURAL NETWORK FOR DEPTH DETERMINATION OF SEPARATIONS BETWEEN A RUBBER MATRIX AND REINFORCING STEEL BELTS

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