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Drift fault recognition method of hot-rolling strip steel based on sound signals

A hot-rolled strip, fault identification technology, applied in metal rolling, metal rolling, length measuring devices, etc., can solve the problems of lack of online detection methods, high noise, and complexity.

Active Publication Date: 2010-09-15
UNIV OF SCI & TECH BEIJING
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the complex production environment on site, the noise is extremely high, and the weak flick sound is easily submerged in the noise. At present, there is no effective online detection method for the flick phenomenon of hot-rolled strip steel at home and abroad, especially the strip flick by acoustic methods. Detection is a pioneering research work at home and abroad

Method used

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  • Drift fault recognition method of hot-rolling strip steel based on sound signals
  • Drift fault recognition method of hot-rolling strip steel based on sound signals
  • Drift fault recognition method of hot-rolling strip steel based on sound signals

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Experimental program
Comparison scheme
Effect test

Embodiment approach 1

[0105] The original signal is resampled at a frequency of 11kHz, the frame length is 1000 data points, and the frame shift is 340 data points. The selection of each parameter is listed in Table 1, from which the recognition rate of tail-flick faults can be 97.47%, and the recognition rate of normal state is 97%.

[0106] Table 1 Selection of parameters

[0107] Number of pivot k

Embodiment approach 2

[0109] The original signal is resampled at a frequency of 11kHz, the frame length is 1000 data points, and the frame shift is 340 data points. The selection of each parameter is listed in Table 2, from which the identification rate of tail-flick fault is 96.2%, and the identification rate of normal state is 96%.

[0110] Table 2 Selection of parameters

[0111] Number of pivot k

Embodiment approach 3

[0113] The original signal is resampled at a frequency of 11kHz, the frame length is 1000 data points, and the frame shift is 340 data points. The selection of each parameter is listed in Table 3, from which the identification rate of tail-flick faults is 98.73%, and the identification rate of normal state is 95%.

[0114] Table 3 Selection of parameters

[0115] Number of pivot k

Confidence test level a

Distribution value F

Total overrun rate ρ

18

0.001

2.336

0.06

[0116] Summarizing the above description, it can be seen that the present invention includes the following steps:

[0117] 1) Preprocessing of re-sampling and framing of the input signal.

[0118] 2) Using Mel frequency cepstrum technology to extract features of the strip flick signal.

[0119] 3) Principal component analysis method and multivariate statistical process control chart are used for feature selection, and a tail-flick recognition model is established.

[0120] 4) Use the built model to recognize the s...

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Abstract

The invention provides a drift fault recognition method of hot-rolling strip steel based on sound signals. The method comprises the following steps of: preprocessing a signal by combining the features of a hot-rolling production line and adopting a resampling and framing technology, carrying out feature extraction on the signal by adopting a Mel frequency cepstrum technology and carrying out feature selection and recognition by adopting a principal component analysis method and a multivariate statistic process T2 control diagram so as to realize the diagnosis of drift faults of the hot-rolling strip steel. The invention has the advantages that the drift phenomenon can be judged accurately and rapidly on line by utilizing an acoustic detection method, the roller replacement time can be reasonably arranged, the roller consumption can be effectively reduced, the production cost can be controlled, and the quality defect prevention capacity and the production operability of the product can be improved.

Description

Technical field [0001] The invention relates to a method for identifying the tail-flick fault of hot rolled strip steel by using acoustic signals. The tail flick of hot rolled steel strip is a kind of abnormal production phenomenon. Online monitoring of the abnormal sound during the tail flick of the strip steel and extracting the characteristics of the acoustic signal to identify the tail flick fault is a novel and effective method for identifying the tail flick fault. Background technique [0002] The tail flick of hot rolled strip is an abnormal production phenomenon caused by flatness control, improper looper control, uneven temperature distribution along the width of the strip, etc. It usually occurs in thin gauges, hard materials, wide-rolled parts and silicon steel. Waiting for production. In the production of hot-rolled strip steel, tail-flicking phenomenon, especially continuous occurrence, will cause the strip tail to fold and break, which will cause great damage to th...

Claims

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Application Information

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IPC IPC(8): B21B38/00
Inventor 阳建宏黎敏李雪瑞陈刚康新成陈翔魏立泽周战郑耀中孟传胜
Owner UNIV OF SCI & TECH BEIJING
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