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 | |
| State | Published - Nov 1 2015 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Geotechnical Engineering and Engineering Geology
- Energy Engineering and Power Technology
- Geochemistry and Petrology
Cite this
}
Ground characterization and roof mapping : Online sensor signal-based change detection. / Bahrampour, Soheil; Rostami, Jamal; Ray, Asok; Naeimipour, Ali; Collins, Craig.
In: International Journal of Mining Science and Technology, Vol. 25, No. 6, 01.11.2015, p. 905-913.Research output: Contribution to journal › Article
TY - JOUR
T1 - Ground characterization and roof mapping
T2 - Online sensor signal-based change detection
AU - Bahrampour, Soheil
AU - Rostami, Jamal
AU - Ray, Asok
AU - Naeimipour, Ali
AU - Collins, Craig
PY - 2015/11/1
Y1 - 2015/11/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84947746041&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84947746041&partnerID=8YFLogxK
U2 - 10.1016/j.ijmst.2015.09.005
DO - 10.1016/j.ijmst.2015.09.005
M3 - Article
AN - SCOPUS:84947746041
VL - 25
SP - 905
EP - 913
JO - International Journal of Mining Science and Technology
JF - International Journal of Mining Science and Technology
SN - 2095-2686
IS - 6
ER -