Real-time online tool wear monitoring method based on wavelet analysis and neural network

A neural network and wavelet analysis technology, applied in manufacturing tools, measuring/indicating equipment, metal processing machinery parts, etc., can solve problems such as inability to characterize local time-frequency characteristics of signals, discrete Fourier transform fence effects, and inability to process fuzzy signals. Achieve fast and efficient detection, shorten learning time, and achieve convenient results

Inactive Publication Date: 2015-12-30
XIAN UNIV OF SCI & TECH
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Problems solved by technology

Fourier transform is an important method for frequency domain analysis, but it has great limitations: Fourier transform extracts frequency features and submerges time features; the time resolution of discrete Fourier transform is fixed, and cannot characterize the time-frequency local features of signals; Discrete Fourier transform has fence effect, spectral leakage and aliasing distortion
However, there are some difficulties in the application of neural networks, such as slow learning speed, local convergence in the learning process, and some fuzzy signals cannot be processed.

Method used

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  • Real-time online tool wear monitoring method based on wavelet analysis and neural network
  • Real-time online tool wear monitoring method based on wavelet analysis and neural network
  • Real-time online tool wear monitoring method based on wavelet analysis and neural network

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Embodiment Construction

[0029] Such as figure 1 and figure 2 Shown, the tool wear real-time on-line monitoring method based on wavelet analysis and neural network of the present invention, comprises the following steps:

[0030] Step 1. Detection and transmission of the three-way cutting force: use the three-way cutting force gauge 1, the resistance strain gauge 2 pasted on the surface of the three-way cutting force gauge 1 and the dynamic resistance strain gauge 3 connected to the resistance strain gauge 2 Measure the three-way cutting force in real time, use the data collector 4 to collect the three-way cutting force, and use the network filter 6 to filter out the environmental noise interference signal and convert the three-way cutting force signal F x , F y and F z Transmission to host computer 5;

[0031] In this embodiment, the three-way cutting dynamometer 1 in step 1 is an octagonal ring type three-way cutting dynamometer, the dynamic resistance strain gauge 3 in step 1 is a SDY2101 dyna...

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Abstract

The invention discloses a real-time online tool wear monitoring method based on wavelet analysis and neutral network. The real-time online tool wear monitoring method comprises steps as follows: step one, detection and transmission of three-way cutting force; step two, wavelet analysis processing; step three, normalization processing; step four, determination of input of the neural network; step five, neural network processing. The method has simple steps and is convenient to implement, the tool wear state can be rapidly and efficiently detected, the processing quality can be guaranteed, and the production efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of tool wear monitoring, in particular to a real-time online monitoring method for tool wear based on wavelet analysis and neural network. Background technique [0002] The automation, flexibility and integration of production have become the development direction of the machinery manufacturing industry. Modern manufacturing equipment represented by CNC machine tools and machining centers has high processing precision and good reliability. The processing quality of workpieces is affected by factors such as machine tools and fixtures. Less, it is more affected by the tool, so good tool performance and condition are very important to ensure the processing quality and improve productivity. [0003] Signal processing technology is the core technology of tool wear status monitoring. It first uses sensors to collect physical quantities that can reflect tool state changes, such as cutting force, cutting power, and ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B23Q17/09
CPCB23Q17/0957
Inventor 张仲华
Owner XIAN UNIV OF SCI & TECH
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