Magnetic shoe internal defect detection method based on wide convolution and recurrent neural network

A technology of cyclic neural network and internal defects, applied in the direction of measuring devices, processing detection response signals, instruments, etc., can solve the problems of difficult detection of internal defects of magnetic tiles, and achieve rapid diagnosis, improve detection efficiency, and ensure product qualification rate effect

Inactive Publication Date: 2021-08-13
SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING
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Problems solved by technology

[0004] In view of the above-mentioned deficiencies in the prior art, the method for detecting internal defects of magnetic tiles based on wide convolution and cyclic neural network provided by the present invention solves the problem that the detection of internal defects of magnetic tiles is difficult

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  • Magnetic shoe internal defect detection method based on wide convolution and recurrent neural network
  • Magnetic shoe internal defect detection method based on wide convolution and recurrent neural network
  • Magnetic shoe internal defect detection method based on wide convolution and recurrent neural network

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[0053] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0054] Such as figure 1 and figure 2 As shown, the internal defect detection method of magnetic tiles based on wide convolution and cyclic neural network includes the following steps:

[0055] S1. Collect the acoustic signals of qualified magnetic tiles and magnetic tiles with known defects, and construct a training set;

[0056] S2. Construct a wide convolution and LSTM cyclic neural network (model); the wide convolutio...

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Abstract

The invention discloses a magnetic shoe internal defect detection method based on a wide convolution and recurrent neural network, and relates to the field of magnetic shoe detection, and the method comprises the following steps: constructing a training set, constructing a wide convolution and LSTM recurrent neural network, training the wide convolution and LSTM recurrent neural network, obtaining a trained detection network, and detecting the acoustic signal of the to-be-detected magnetic shoe through the trained detection network to complete the internal defect detection of the to-be-detected magnetic shoe. According to the method, specialist knowledge and complex signal processing and feature selection are not needed, spatial-temporal feature extraction and classification can be directly carried out on original signals in an end-to-end mode by utilizing the wide convolution and the LSTM recurrent neural network, and therefore the target of identifying the internal defects of the magnetic shoe is achieved.

Description

technical field [0001] The invention relates to the field of magnetic tile detection, in particular to a method for detecting internal defects of magnetic tiles based on wide convolution and cyclic neural networks. Background technique [0002] The permanent magnet DC motor mainly relies on the generation of the constant magnetic field for the magnetic tile, which is a tile-shaped ferrite. In the manufacturing process of magnetic tiles, due to the complex production process, structural defects are prone to occur, resulting in defective products. Compared with qualified magnetic tiles, these defective products with structural defects will seriously affect the operating efficiency and service life of the motor. Therefore, how to effectively remove these defective products is the key to ensure the quality of finished magnetic tiles. The internal defect of the magnetic tile is the most prominent and main structural defect problem. Due to the characteristics of random distribut...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N29/04G01N29/44
CPCG01N29/045G01N29/44G01N29/4481
Inventor 黄沁元李强周颖杨天
Owner SICHUAN UNIVERSITY OF SCIENCE AND ENGINEERING
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