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Acoustic emission source positioning method based on multidimensional kernel density estimation

A technology of nuclear density estimation and acoustic emission source, which is used in material analysis using acoustic emission technology, processing response signals of detection, and material analysis using acoustic/ultrasonic/infrasonic waves, which can solve problems such as the impact of abnormal arrival data.

Active Publication Date: 2019-10-25
CENT SOUTH UNIV
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Problems solved by technology

[0004] The technical problem solved by the present invention is to propose an acoustic emission source localization method based on multi-dimensional kernel density estimation, which is easy to implement and has high positioning accuracy, in view of the problem that the existing acoustic emission positioning technology is easily affected by abnormal arrival data

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  • Acoustic emission source positioning method based on multidimensional kernel density estimation
  • Acoustic emission source positioning method based on multidimensional kernel density estimation
  • Acoustic emission source positioning method based on multidimensional kernel density estimation

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Embodiment Construction

[0062] The coordinates of an acoustic emission source are preset as S(110, 160, 180), and the coordinates of the sound source are A(0,0,0), B(300,0,0), C(300,300,0), D( 0,300,0), E(0,0,300), F(300,0,300), G(300,300,300), H(0,300,300), I(300,150,150) surrounded by 9 acoustic emission sensors. The unit is mm. The wave speed is unknown. In this experiment, a set of arrival data is generated by simulation method, and an error with a variance of 0.2 μs is added to the obtained arrival data to simulate the impact of environmental noise on positioning. In addition, a large error of ±5 μs is randomly added to an arrival data , to simulate the interference of outliers. A set of arrival data generated through the above random process is: 38.38, 42.90, 40.89, 50.75, 53.10, 53.13, 55.27, 59.41, 61.55, the unit is μs.

[0063] This method is described in detail with this example. For the convenience of clearly illustrating the problem, be divided into the following five steps and set f...

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Abstract

The invention discloses an acoustic emission source positioning method based on multidimensional kernel density estimation. The acoustic emission source positioning method comprises the steps of: firstly, combining arrival time data of an acoustic emission sensor to obtain a plurality sets of arrival time data, constructing corresponding properly determined equation sets according to different arrival time data sets, solving the equation sets to obtain a plurality of sets of closed-form solutions, and filtering out the closed-form solutions containing imaginary roots to obtain r0 preliminary positioning results; secondly, excluding abnormal positioning results in the preliminary positioning results, and finally acquiring r preliminary positioning results; and thirdly, constructing a multidimensional kernel density estimation function of acoustic emission source coordinates theta by utilizing the r preliminary positioning results, and calculating a maximum value point of the multidimensional kernel density estimation function, wherein the maximum value point is the optimal acoustic emission source positioning result. The acoustic emission source positioning method disclosed by the invention has high positioning precision.

Description

technical field [0001] The invention relates to an acoustic emission source localization method based on multi-dimensional kernel density estimation. [0002] technical background [0003] Acoustic emission positioning technology is widely used in structural integrity monitoring, material damage mechanism research, mine risk warning and other fields. However, due to the complex experimental conditions and noisy construction environment, the AE waveform containing the arrival information detected by the AE sensor during the AE detection (location) process is often affected by interference signals, resulting in abnormal arrival. In addition, the subjectivity of artificial time picking and the limitations of existing time picking algorithms also make the acquired time data often mixed with abnormal data. Moreover, these abnormal data will seriously affect the accuracy of positioning results. For this reason, the invention patent with the application number CN201510973875.4 pro...

Claims

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Application Information

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IPC IPC(8): G01N29/14G01N29/44
CPCG01N29/14G01N29/4472G01N2291/0289
Inventor 周子龙芮艺超周静杜雪明臧海智林成龙
Owner CENT SOUTH UNIV
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