Method and device for fault classification of micro vibration motor defects based on convolutional neural network

A technology of convolutional neural network and vibration motor, which is applied in the direction of biological neural network model, neural learning method, neural architecture, etc., can solve the problems of difficulty in ensuring accuracy and low efficiency, and achieve high-precision detection, high detection accuracy, and high The effect of detection accuracy

Active Publication Date: 2020-04-03
SICHUAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] Aiming at the problems of low efficiency and difficulty in ensuring the accuracy of defect detection of micro vibration motors based on artificial vision, the purpose of the present invention is to provide a method and device for classifying defects and faults of micro vibration motors based on convolutional neural network. While accurately classifying micro-vibration motor defects and faults, it simplifies operation difficulty and improves detection efficiency

Method used

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  • Method and device for fault classification of micro vibration motor defects based on convolutional neural network
  • Method and device for fault classification of micro vibration motor defects based on convolutional neural network
  • Method and device for fault classification of micro vibration motor defects based on convolutional neural network

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Embodiment 1

[0044] The miniature vibrating motor fault classification device provided in this embodiment, such as Figure 1 to Figure 3 As shown, it includes a miniature vibration motor fixture 1, a micro control unit 2, a power supply 3, an acquisition resistor 4, a start resistor, a data acquisition card 5 and a computer 6.

[0045] Such as image 3 As shown, the micro-vibration motor fixture 1 is provided with a plurality of slots 11 for installing the micro-vibration motor 7, and two electrodes 12 corresponding to the electrical ports of the micro-vibration motor are designed on the slot wall on one side of the slot. It matches the appearance of the micro vibration motor; the eccentric block of the micro vibration motor extends from the wall on the other side of the card slot, and the wall of the card slot is designed with a limit structure to prevent the micro vibration motor from moving axially. It is a limiting piece fixed on the inner wall of the card slot, and a limiting opening...

Embodiment 2

[0048] In this embodiment, the labview software is used to collect the voltage signal, and the OpenCV support package of python is used to process the collected voltage signal image. All computers use serial port communication, the host uses its own serial port, the labview software uses visa serial port communication support package, and python uses pyseries serial port communication support package.

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Abstract

The invention discloses a defect classification method and device of a micro-vibration motor based on a convolutional neural network. The collected voltage signal images connected in series to both ends of the collection resistance of the micro-vibration motor energization circuit are input to the trained convolutional neural network. The model can realize the accurate identification of the defect types of the micro vibration motor. The whole process is an automatic identification operation, which does not require too many staff to participate in the entire generation process, which greatly improves the detection efficiency and reduces labor production costs.

Description

technical field [0001] The invention belongs to the technical field of machine defect detection, and relates to a defect detection technology for micro vibration motors based on deep learning, in particular to a classification method and device for defects and faults of micro vibration motors based on convolutional neural networks. Background technique [0002] Micro vibration motors are widely used in electronic devices such as mobile phones and smart wearables. With the rapid development of interactive electronic devices in my country, the demand for micro-vibration motors is increasing day by day, and the annual demand reaches more than 2 billion. How to quickly detect defective products in the production line has become a bottleneck limiting the output of motors. [0003] The mechanical vibration caused by the bearing defect of the micro vibration motor will cause the eccentric oscillation of the air gap width, which in turn will cause the change of the magnetic flux de...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/34G06K9/00G06K9/32G06K9/38G06K9/62G06N3/04G06N3/08G06T5/30
Inventor 方夏黄思思刘剑歌王杰冯涛
Owner SICHUAN UNIV
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