Analysis of signal characteristics from rock drilling based on vibration and acoustic sensor approaches. (November 2018)

• Record Type: Journal Article
• Authors: Qin, Min; Wang, Kai; Pan, Kai; Sun, Tianxi; Liu, Zhiguo
• Is Part Of: Applied acoustics. Volume 140(2018)
• Page Start: 275
• Page End: 282
• Publication Date: 2018-11
• Subjects: PDC bit -- Vibration signal -- Acoustic signal -- Rock drilling -- Lithological recognition -- Signal characteristic; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2018.06.003
• Languages: English
• ISSNs: 0003-682X

Abstract

Highlights: Two methods to distinguish the drilling signal characteristics were investigated. Time-frequency analyses were proposed to analyze signal characteristics. Acoustic method presents a better signal-to-noise ratio than vibration method. Abstract: Lithological recognition is of great significance in oil drilling fields. To investigate the relationship between rock properties and the vibro-acoustic signal characteristics generated by drilling, a rock drilling vibration measurement system has been developed, and a relative drilling test is conducted indoors. This paper illustrates the application of a vibration sensor and a special wideband acoustic sensor method to distinguish the specific time–frequency characteristics generated by drilling in different types of rock. Furthermore, an intuitive comparison of these two approaches is performed. In particular, an acoustic focusing device was designed to assist the wideband acoustic condenser microphone in detecting specific signals during the drilling process. In addition, time-domain and time–frequency analyses were proposed to reveal the differences in signal characteristics generated by different kinds of rock. The results indicate that both the vibration spectral characteristics and the acoustic spectral characteristics from 4 types of rock show significant differences, which may be promising for lithological recognition using the feature model. However, the acoustic sensor approach, benefiting from the specially designed acoustic focusing device, presents a better signal-to-noise ratio than the vibration sensor approach.