During the operation of each machine, there are dynamic effects causing vibrations. Such a device is also an experimental horizontal drilling stand with aggregates, i.e., a direct current motor (DC), a pump, and a hydro-generator. During their operation, unwanted vibration acceleration signals are generated. It is clear that the accompanying vibration signal carries integrating information about the current state of the drilling rig. Vibration signal processing methods for the time and

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... domains were used. The results of time-domain processing showed significant differences in time waveforms, statistical characteristics, and auto-correlation functions. The auto-correlation function pointed to the periodicity and dependence of the vibrational signal samples. Based on the acquired knowledge, the signals were classified, and a strong source of vibration was determined. Noise is superimposed on the harmonic components of the signals. Amplitude and power spectra were constructed in the frequency domain. Dominant frequencies were identified for each investigated mode in the operating mode. Power spectra removed less significant frequencies and focused on the dominant ones. Time-frequency spectrograms revealed significantly higher frequency bands. The proposed methods can be implemented in diagnosing the operation of the machine and aggregates, determining the source of the greatest vibrations, wear of parts of the equipment such as the drill bit, and recognition of the overall condition of the equipment.