Estimating rock properties using sound levels produced during drilling

Vardhan, Harsha; Adhikari, G. R.; Raj, M. Govinda

doi:10.1016/j.ijrmms.2008.07.011

Cited by 56 publications

(14 citation statements)

References 12 publications

(11 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When the drilling equipment operates in noload mode but also in the process of rock drilling, a vibroacoustic signal is generated. Therefore, it is reasonable to assume that the vibroacoustic signal generated by the technological equipment will carry current information characterizing the state of the equipment and the drilling process [35].…”

Section: Experimental Results and Analysismentioning

confidence: 99%

Evaluating Noise Sources in a Working Environment when Disintegrating Rocks by Rotary Drilling

Flegner¹,

Kačur²,

Durdán³

et al. 2019

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

The mechanical disintegration of rocks plays an irreplaceable role in the exploration, preparation, and mining of minerals resources in geological and engineering surveys. When disintegrating by rotary drilling, the disintegration tool interacts with the rock and converts the mechanical energy to thermal energy caused by the friction of the disintegration tool on the rock. Consequently, undesirable accompanying sounds occur in the process of disintegration of the rock by drilling. These include vibrations that show up in the working environment as noise. The noise generated during rotary drilling can be scanned as an acoustic signal. From above, it is possible to say that noise and vibration have a direct negative impact on the machinery personnel, on the working environment and on the environment. At present, research in the field of the disintegration of rocks by rotary drilling is directed at analyzing the factors affecting the disintegration of rocks and the working environment. This article analyzes experimental measurements carried out on a horizontal drilling tool. Measured vibroacoustic signals in different operating modes will be processed in the time, frequency, and time-frequency domains.

show abstract

Section: Experimental Results and Analysismentioning

confidence: 99%

Evaluating Noise Sources in a Working Environment when Disintegrating Rocks by Rotary Drilling

Flegner¹,

Kačur²,

Durdán³

et al. 2019

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

“…Accordingly, the AE signal processing methods can be classified into three categories: (i) signal processing, (ii) feature extraction, and (iii) pattern recognition. The most important and widely used (Qin et al, 2018) × (Karakus & Perez, 2014) × × × × (Bastari et al, 2011) × (Parsian et al, 2017) × × × (Marinescu & Axinte, 2009) × × (Xiao, Hurich et al, 2018) × (Li et al, 2018) × × (Buj-Corral et al,, 2018) × (Shaffer et al,, 2018) × × × (Wang et al, 2017) × × (Rivero et al, 2008) × (Flegner et al, 2014) × (Feng & Yi, 2017) × (Yari et al, 2017) × (Yari & Bagherpour, 2018 (a&b)) × (Shreedharan et al, 2014) × (Kostur & Futo, 2007) × ( Kawamura et al, 2017) × (Pedrayes et al, 2018) × × (Gradl et al, 2012) × × × (Vardhan et al, 2009) × × × (Beheshtizadeh et al, 2017) × (Miklusova et al, 2006) × × × × (Goyal & Pabla, 2016) × (Liew & Wang, 1998) × × (Kong et al, 2015) × (Jain et al, 2001) The Mining-Geology-Petroleum Engineering Bulletin and the authors ©, 2019, pp. 19-32, DOI: 10.17794/rgn.2019.4.3 methods of the first category (signal processing) include: time series statistical models, Short Time Fourier Transform (STFT), Fast Fourier Transform (FFT), Wavelet Packet Decomposition (WPD), Hilbert-Huang transform (HHT), Wigner-Ville distribution, signal spectrum analysis, Adaptive Line Enhancer (ALE), wavelet transform, and the Peak-Hold-Down-Sample (PHDS) algorithm.…”

Section: Acoustic Signal Processing Feature Extraction and Pattern Rmentioning

confidence: 99%

Application of Acoustic Emission (Ae) in Mining and Earth Sciences: A Review

Khoshouei

Bagherpour

2019

MGPB

View full text Add to dashboard Cite

One of the most important products of the majority of tools, processes and, phenomena in mining engineering and earth sciences are high-frequency elastic waves, often referred to as acoustic waves. These acoustic waves can be a useful tool for prediction and measurement, monitoring and diagnosis. Due to the importance of engineering activities that should be specific, measurable, available, reliable and time-based (SMART), Acoustic Emission (AE) techniques can be integrated into engineering operations such as excavation to give exact estimations or simplify some aspects of investigations. Hence, these techniques are expected to play an increasing role in the detection, monitoring, and measurement in engineering applications. With the development of acoustic signal processing methods in earth sciences and the growing need for accurate, fast, and cost-effective prediction, monitoring and measurement methods, AE tools and techniques are expected to turn into powerful alternatives to current methods. The purpose of this paper is to review the application of the acoustic methods as a tool in various projects. For this purpose, the application of AE methods has been reviewed in different fields related to earth sciences including mining engineering, drilling engineering, geology, petroleum engineering, and other related fields. According to the purpose of using these methods, the application of AE is divided into three groups: prediction and estimation, monitoring and performance assessment, and detection. The use of AE methods, among other laboratory or in-situ methods, is very fast and accurate, and by only installing specific sensors with data logging equipment, it has been able to process and analyse data online and remotely. Finally, the possibility of using AE techniques in design and calculating in various projects and as a tool for decision making was evaluated.

show abstract

“…The specific energy (SE) consumption during drilling can be calculated as a function of the measured drilling variables as follows (Teale 1965): Teale's work, followed by others, concludes that other factors such as hole size, mode of rock breakage and bit type could all effect specific energy (Rabia 1982;Vardhan et al 2009). The latter information was used by industry to estimate strata recognition and blastability index (CATERPILLAR 2016a(CATERPILLAR , 2016bLilly 1986).…”

Section: Specific Energymentioning

confidence: 99%

The use of soft computing methods for the prediction of rock properties based on measurement while drilling data

Başarır¹,

Wesseloo²,

Karrech³

et al. 2017

Proceedings of the International Conference on Deep and High Stress Mining

View full text Add to dashboard Cite

Due to recent technological advancements drilling operations conducted for different purposes such as exploration, blasting and even grouting are not considered as auxiliary operations any longer. On the contrary, nowadays onsite drilling operations are considered as important resources for getting more information about rock properties. Many researchers have been working on measurement while drilling (MWD) techniques and their possible use for the prediction of rock mass properties. This paper presents a literature survey on the use of MWD technology for the prediction of rock mass properties. The survey indicates that the analysis and interpretation of MWD data is as important as recording the data. Both blackbox modelling such as regression and soft computing or grey-box modelling techniques are used as a tool for the analysis and interpretation of MWD data. This paper presents a case study showing the integration of soft computing methods such as adaptive fuzzy inference system (ANFIS) with MWD data for the prediction of rock mass properties such as rock quality designation (RQD). The results indicated that such soft computing methods can successfully be used as an analysis and interpretation tool.

show abstract

Estimating rock properties using sound levels produced during drilling

Cited by 56 publications

References 12 publications

Evaluating Noise Sources in a Working Environment when Disintegrating Rocks by Rotary Drilling

Evaluating Noise Sources in a Working Environment when Disintegrating Rocks by Rotary Drilling

Application of Acoustic Emission (Ae) in Mining and Earth Sciences: A Review

The use of soft computing methods for the prediction of rock properties based on measurement while drilling data

Contact Info

Product

Resources

About