Patrik Flegner, Ján Kačúr, Gabriel Wittenberger, Milan Durdán, Marek Laciak
Rotary rock drilling generates vibration signals that capture the dynamic behavior of the drilling system, the interaction between the tool and the rock, and the progression of tool wear. These signals, traditionally considered undesirable, have become a key source of information for condition monitoring and predictive maintenance. This study experimentally investigates vibration sources and diagnostic indicators using a laboratory horizontal drilling stand equipped with accelerometers and controlled operating regimes. Six regimes were evaluated, ranging from idle operation of individual aggregates (motor, pump, hydrogenerator) to drilling of concrete and granite under defined process parameters. Vibration data were analyzed in the time, frequency, and time–frequency domains using RMS, variance, spectral centroid, spectral entropy, FFT-based spectra, autocorrelation, cross-correlation, and spectrograms. The results confirm the research hypothesis that selected vibration-based indicators correlate with tool degradation. Increased RMS values, higher variance, reduced correlation symmetry, and a shift of spectral energy above 6 kHz reliably reflect wear progression and changes in the dynamic response of the system. Spectrograms further reveal transient phases and redistribution of vibration energy during drilling. The findings demonstrate that vibration measurements enable the identification and separation of vibration sources related to aggregates and processes. The extracted diagnostic features form a basis for intelligent monitoring and predictive algorithms in rotary drilling, supporting advanced condition monitoring strategies within Industry 4.0.