Ground characterization and roof mapping: Online sensor signal-based change detection

Soheil Bahrampour; Jamal Rostami; Asok Ray; Ali Naeimipour; Craig Collins

doi:10.1016/j.ijmst.2015.09.005

Ground characterization and roof mapping: Online sensor signal-based change detection

Soheil Bahrampour, Jamal Rostami, Asok Ray, Ali Naeimipour, Craig Collins

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and location & frequency of joints or voids. This paper focuses on improving rock characterization algorithms for instrumented roof-bolter systems. For this purpose, an improved void detection algorithm is proposed, where the underlying theory is built upon the concept of mean change detection based on the feed pressure signals. In addition, the application of acoustic sensing for void detection is examined and it is shown that the variance of the filtered acoustic signal is correlated to the strength of the material being drilled. The proposed algorithm has been validated on the data collected from full-scale drilling tests in various concrete and rock samples at the J. H. Fletcher facility.

Original language	English (US)
Pages (from-to)	905-913
Number of pages	9
Journal	International Journal of Mining Science and Technology
Volume	25
Issue number	6
DOIs	https://doi.org/10.1016/j.ijmst.2015.09.005
State	Published - Nov 2015

All Science Journal Classification (ASJC) codes

Geotechnical Engineering and Engineering Geology
Energy Engineering and Power Technology
Geochemistry and Petrology

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title = "Ground characterization and roof mapping: Online sensor signal-based change detection",

abstract = "Measurement while drilling systems are becoming an important part of excavation operations for rock characterization and ground support design that require reliable information on rock strength and location & frequency of joints or voids. This paper focuses on improving rock characterization algorithms for instrumented roof-bolter systems. For this purpose, an improved void detection algorithm is proposed, where the underlying theory is built upon the concept of mean change detection based on the feed pressure signals. In addition, the application of acoustic sensing for void detection is examined and it is shown that the variance of the filtered acoustic signal is correlated to the strength of the material being drilled. The proposed algorithm has been validated on the data collected from full-scale drilling tests in various concrete and rock samples at the J. H. Fletcher facility.",

author = "Soheil Bahrampour and Jamal Rostami and Asok Ray and Ali Naeimipour and Craig Collins",

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AU - Rostami, Jamal

AU - Ray, Asok

AU - Naeimipour, Ali

AU - Collins, Craig

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