The characterization of solid particles in slurry flows is critical for the timely optimization of chemical and petroleum production, yet the development of an efficient characterization method remains challenging. In this work, a novel triaxial vibration method was developed to evaluate the features of slurry flow particles. Particle.wall collision behaviors were analyzed by temporal statistical and peak searching methods, and the particle features were distinguished from the random turbulence noise features of slurry flow in both the global and the local time.frequency 2-D planes. The collision frequency features were optimized by the noncoherence and signal-to-noise ratio (SNR) analysis method in different vibration directions along the x-axis (42.5-48.5 kHz, excluding 45-46 kHz), y-axis (46-48.5 kHz), and z-axis (41.6-42.9 kHz). Corresponding verification experiments were performed, and good agreement was found between the test conditions (average sand and glass size of 380 lm, particle mass rate of 0.27-1.80 g/s, flow velocity of 2.2-3.0 m/s) and vibration levels in three directions. The method was further evaluated by autoclassification with high recognition rates of 85% for sand and 95% for glass. The verified linear relations between the solid particle mass rates and vibration level presented low error rates of 15.97% (z-axis), 10.65% (y-axis), and 6.94% (x-axis) for sand and 10.32% (z-axis), 8.57% (y-axis), and 8.19% (x-axis) for glass, and more particle features were obtained. Therefore, this work complements existing studies and is expected to support the development of particle characterization in three-dimensional space.