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Tool abrasion monitoring method based on wavelet denoising and Hilbert-Huang transformation

A wavelet denoising and tool wear technology, applied in the field of signal processing, can solve problems such as energy leakage and insufficient self-adaptation, and achieve strong adaptability, high self-adaptability, and good application prospects

Inactive Publication Date: 2014-08-06
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

The present invention proposes a method for processing vibration signals using Hilbert-Huang transform on the basis of wavelet denoising, which can overcome the problems of energy leakage and insufficient self-adaptation during signal transformation, and can improve the relative signal energy time and frequency distributions for precise analysis

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  • Tool abrasion monitoring method based on wavelet denoising and Hilbert-Huang transformation
  • Tool abrasion monitoring method based on wavelet denoising and Hilbert-Huang transformation
  • Tool abrasion monitoring method based on wavelet denoising and Hilbert-Huang transformation

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Embodiment Construction

[0039] A tool wear monitoring method based on wavelet denoising and Hilbert-Huang transform in this embodiment adopts the following steps:

[0040] Step 1: Collect the vibration signals of several groups of tools of the same type in three time periods during operation. The three time periods correspond to the initial wear, normal wear and severe wear of the tool respectively; the sampling time of the three time periods is the same; different groups have the same The cutting parameters during the operation of the type tool are different.

[0041] In this embodiment, using the orthogonal test method, according to the three cutting elements and the designation plan of the tool wear amount, as shown in Table 1 and Table 2, the cutting parameters of the milling machine are respectively set, that is, the spindle speed, the feed rate, the cutting depth, and the vibration sensor is used to control the machine tool. During the operation process, 16 groups of vibration signals were coll...

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Abstract

The invention provides a tool abrasion monitoring method based on wavelet denoising and Hilbert-Huang transformation. According to the method, on the basis of wavelet denoising, the Hilbert-Huang transformation method is used for analyzing signals acquired in the machine tool operating process; according to an amplitude average value, obtained through EMD, of each IMF component and a time-frequency spectrum and a marginal spectrum which are obtained through Hilbert transformation, a normal state of a tool and an abrasion state of the tool are compared, and obvious characteristics are obtained. The self-adaptability of the method is much higher than that of other characteristic extraction methods; according to the method, the defects of high-frequency resolution are overcome, and meanwhile signal characteristics further retain all physical significances contained in original signal characteristics.

Description

technical field [0001] The invention relates to the relevant field of signal processing technology, especially vibration signal processing, and is a tool wear monitoring method based on wavelet denoising and Hilbert-Huang transformation. Background technique [0002] In a modern manufacturing system, in order to ensure the safety and processing quality of high-investment automatic processing equipment, it is urgent to solve the monitoring problem during processing. Tool state change is one of the most common faults in machining process. Due to the diversity of processing conditions, the variability of cutting parameters, and tool wear and other factors, tool condition monitoring has become an important link in the monitoring of the entire production process. Tool condition monitoring technology is based on modern sensor technology, signal processing technology, computer technology and manufacturing technology. It is an emerging technology developed on the basis of advanced ...

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Application Information

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IPC IPC(8): B23Q17/09B23Q17/12
CPCB23Q17/0957B23Q17/12B23Q17/0971B23Q17/0995
Inventor 孙惠斌牛伟龙王俊阳孙小光田国良
Owner NORTHWESTERN POLYTECHNICAL UNIV
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