Abstract: The present disclosure provides a method for obtaining a milling particle gradation prediction model, a prediction method and a device. The method includes: sieving a plurality of groups of test particles obtained by a plurality of milling tests to obtain a sieve residual mass ratio corresponding to each of a plurality of sieves after performing milling tests on an asphalt layer; calculating a characteristic parameter of a cutting graph of the milling rotor according to arrangement of cutter teeth of the milling rotor, a rotational speed, a forward speed, and a milling depth of the milling rotor; establishing, by regression analysis, a functional relation between the sieve residual mass ratio corresponding to each sieve and the characteristic parameter according to the rotational speed, the forward speed and the milling depth; and normalizing the functional relation to obtain the milling particle gradation prediction model.

Abstract: A cutter holder measuring tool includes: a base with a positioning point configured to be detected by a detecting device; and a mounting assembly, including a sleeve, a positioning pin and an end plate, wherein two axial ends of the sleeve are connected to the base and the end plate respectively, the end plate is configured to abut against a mounting surface of a cutter holder of a milling rotor, the mounting surface is a surface, facing a tip of a cutter, of the cutter holder, the positioning pin is inserted into the sleeve and a mounting hole, for the cutter to insert, of the cutter holder, the positioning pin is movable along an axial direction of the sleeve, and a diameter of the positioning pin changes along the axial direction of the sleeve, so a center of the positioning pin is collinear with a center of the mounting hole.