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Intelligent gearbox fault diagnosis method based on multi-channel self-calibration convolutional neural network

A convolutional neural network and fault diagnosis technology, applied in neural learning methods, biological neural network models, neural architectures, etc. The effect of reducing the probability of fault diagnosis errors and reducing the use of labor

Pending Publication Date: 2022-07-29
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS +1
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The traditional convolutional neural network cannot differentiate the features of each channel, which may cause the network to learn similar feature forms

Method used

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  • Intelligent gearbox fault diagnosis method based on multi-channel self-calibration convolutional neural network
  • Intelligent gearbox fault diagnosis method based on multi-channel self-calibration convolutional neural network
  • Intelligent gearbox fault diagnosis method based on multi-channel self-calibration convolutional neural network

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Embodiment Construction

[0061] The invention provides an intelligent fault diagnosis method for a gearbox based on a multi-channel self-calibration convolutional neural network, which combines information fusion and a self-calibration convolutional neural network to perform effective fault diagnosis for a single fault of the gearbox under the same rotational speed condition. Including: after the dimensional increase of the Grammy angle field data, the one-dimensional vibration signals measured by multiple sensors are converted into two-dimensional data, and the two-dimensional data is converted into a grayscale image as input, and a data set is established and divided into training set and test set. Build a self-calibration convolution module, build a self-calibration convolutional neural network, and extract data features. Set the fusion layer to convert the output of the self-calibration convolutional neural network into one-dimensional data and fuse the feature information. Set up fully connected...

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Abstract

The invention discloses a gearbox intelligent fault diagnosis method based on a multichannel self-calibration convolutional neural network. The gearbox intelligent fault diagnosis method comprises the following steps: increasing dimension of glassmeter angle field data, converting one-dimensional vibration signals of a plurality of sensors into two-dimensional data, converting the two-dimensional data into gray level images as input, establishing a data set, and dividing the data set into a training set and a test set. And constructing a self-calibration convolutional neural network, and extracting data features. And setting a fusion layer, converting the output of the self-calibration convolutional neural network into one-dimensional data, and fusing feature information. And setting a full connection layer, and mapping the distributed features to a sample marking space. And constructing a Softmax feature classifier to classify the extracted features. And learning the network by using the training set, and testing the trained network by using the test set to realize fault diagnosis of the gearbox. The self-calibration convolutional neural network model provided by the invention is combined with an information fusion method, and can effectively diagnose a single fault of the gearbox under the same rotating speed working condition.

Description

technical field [0001] The invention belongs to the technical field of gearbox vibration signal intelligent fault diagnosis, and relates to a gearbox intelligent fault diagnosis method based on a multi-channel self-calibration convolutional neural network. Background technique [0002] With the rapid development of China's information technology and industrial generation technology, modern mechanical industrial equipment presents the characteristics of large-scale, high-speed, complex, intelligent and integrated, its functions are constantly improved, and its internal structure is increasingly sophisticated. Gearbox is the most widely used important component in mechanical equipment, and its smooth operation is crucial to the normal operation of the entire equipment. However, because the gearbox is often in harsh working conditions such as variable speed and high load, it is very prone to damage or even failure, resulting in huge economic losses and casualties. [0003] Cla...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06N3/048G06N3/045G06F2218/12
Inventor 李舜酩王艳丰张名武龚思琪滕光蓉
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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