The particle distribution characteristics of chips are an important parameter affecting dredging transportation. This paper explores the particle distribution of chips through cutting tests, analyzes the particle size distribution characteristics and particle size composition, and uses the particle analysis curve to obtain the characteristic particle size value and gradation relationship of chips. And we further analyzed the relationship between particle size, cutting depth and cutting force. At the same time, the cutting depth is estimated by the particle size, the cutting force and cutting power consumption are analyzed and the construction is guided. The research shows that the particle size distribution curves at different cutting depths present a decreasing quadratic curve trend, and the particle size composition is not uniform and the gradation is poor. The particle size will gradually increase with the increase of cutting depth and cutting force, but the change degree of each characteristic particle size is different with the cutting depth and cutting force. Based on this, the relationship between particle size, cutting depth and cutting force is proposed, combined with the change of power consumption The engineering depth of cut was suggested and provided valuable data for numerical simulation and tooth design.


The theory and related mechanism of rock breaking by cutter tooth cutting are widely used in mining engineering, tunnel engineering, rock dredging engineering and so on. The study mainly discusses the physical and mechanical properties of rock, the change of cutting parameters and energy in the cutting process and the cutting efficiency (Ouyang, 2013; Ouyang, 2018; Zhang, 2019). There is little research on the relationship between the particle size and cutting parameters of rock chips.

In the rock dredging project, it is often necessary to deal with the broken rock debris and transport the debris to the discharge site through the dredging cutter suction ship pipeline. In the study of the size distribution of rock fragments after cutter tooth cutting, it is determined by Song that the Rosin-Rammler distribution function is consistent with the rock chip particle size distribution by on-site driving tests, measurement, screening, and other methods. This is done by combining probability and statistical theory with the theoretical particle size distribution model (Song, 2008). By examining the drilling cuttings' particle size distribution, Yi was able to optimize both the equipment load computation and the structural design. Studying the correlation between chip size distribution and cutting parameters is therefore crucial in the process of cutting cutter tooth (Yi, 2007). Yi took cuttings samples from 7 wells in the Liaohe Oilfield in China with a depth of less than 3500 m, and analyzed the particle size distribution of rock samples with an average particle size of more than 74 μm. The results show that the cuttings are obviously flaky, and the particle size distribution curve is mainly related to the formation rock and the drill bit (Yi, 2013). Mohammadi et al. analyzed the shape and size distribution of chips generated in laboratory-scale rock cutting experiments and their relationship to cutting geometry and rock machinability. The results obtained from the chip analysis showed that 85.6% of the selected chip fragments were very plate-like and very blade-like. As expected based on rock fragmentation and grinding theory, there is an inverse exponential correlation between specific energy and particle size indices including CI, dMPS, d50, and d′ (Mohammadi, 2019).

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