Improving the capability of detecting joints and fractures in rock mass from roof bolt drilling data by using wavelet analysis

2019 ◽  
Vol 20 (1) ◽  
pp. 97 ◽  
Author(s):  
Wenpeng Liu ◽  
Samer S. Saab <suffix>Jr.</suffix> ◽  
Jamal Rostami ◽  
Asok Ray
Keyword(s):  
Rock Mass ◽  
Wavelet Analysis ◽  
Roof Bolt ◽  
Drilling Data

scholarly journals Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5522
Author(s):  
Krzysztof Lalik ◽  
Ireneusz Dominik ◽  
Paweł Gut ◽  
Krzysztof Skrzypkowski ◽  
Waldemar Korzeniowski ◽  
...  
Keyword(s):  
Rock Mass ◽  
Stress State ◽  
Testing System ◽  
Salt Mine ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Roof Bolt ◽  
Excited System ◽  
Intelligent Filtering ◽  
Non Destructive

This article presents the application of a self-excited acoustic SAS system for non-destructive testing (NDT) for roof-bolt housings in laboratory and real mine conditions. The proposed system with a filtering mechanism was applied to the J64-27 composite anchors. The conducted tests allowed successful confirmation of the usefulness of the system in the detection of rod defects, damage of the mechanism coupling the anchor to the rock mass and testing of the stress state of the anchor itself. The proposed filtering system allowed eliminating the effect of jump change of frequency in the limit cycle of self-excited system. The proposed method is a novel solution for safety diagnostics of bolt housings in mining applications.

scholarly journals Correlation between Drilling Data and Rock Mass Properties Focused on the Effect of Hole Length

2004 ◽  
Vol 120 (9) ◽  
pp. 508-514 ◽  
Author(s):  
Masayuki YAMASHITA ◽  
Katsunori FUKUI ◽  
Seisuke OKUBO
Keyword(s):  
Rock Mass ◽  
Rock Mass Properties ◽  
Mass Properties ◽  
Drilling Data

Classification of Acceleration Waveforms during Walking by Wavelet Transform

1997 ◽  
Vol 36 (04/05) ◽  
pp. 356-359 ◽  
Author(s):  
M. Sekine ◽  
M. Ogawa ◽  
T. Togawa ◽  
Y. Fukui ◽  
T. Tamura
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Center Of Gravity ◽  
Dynamic Responses ◽  
Sequential Data ◽  
Acceleration Signal ◽  
Continuous Dynamic

Abstract:In this study we have attempted to classify the acceleration signal, while walking both at horizontal level, and upstairs and downstairs, using wavelet analysis. The acceleration signal close to the body’s center of gravity was measured while the subjects walked in a corridor and up and down a stairway. The data for four steps were analyzed and the Daubecies 3 wavelet transform was applied to the sequential data. The variables to be discriminated were the waveforms related to levels -4 and -5. The sum of the square values at each step was compared at levels -4 and -5. Downstairs walking could be discriminated from other types of walking, showing the largest value for level -5. Walking at horizontal level was compared with upstairs walking for level -4. It was possible to discriminate the continuous dynamic responses to walking by the wavelet transform.

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