The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 02, 2026

Filed:

Nov. 18, 2022
Applicant:

X Development Llc, Mountain View, CA (US);

Inventors:

Ray Anthony Nagatani, Jr., San Francisco, CA (US);

Allen Richard Zhao, Mountain View, CA (US);

Antonio Raymond Papania-Davis, Oakland, CA (US);

Weishi Yan, Oakland, CA (US);

Brian Howell, Berkeley, CA (US);

Jeffrey Bush, Los Altos, CA (US);

Charles Stephen Spirakis, Mountain View, CA (US);

Assignee:

X Development LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B02C 25/00 (2006.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01);
U.S. Cl.
CPC ...
B02C 25/00 (2013.01); G05B 13/027 (2013.01); G05B 13/042 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for in-process adjustment to crushing systems. A method includes obtaining pre-crush particle data indicating characteristics of a portion of particles before crushing the portion of particles with a crushing system; obtaining settings data indicating one or more settings of the crushing system; obtaining post-crush particle data indicating characteristics of the portion of particles after crushing the portion of particles; and training a prediction model using the pre-crush particle data, the settings data, and the post-crush particle data, comprising: processing, using the prediction model, the pre-crush particle data and the settings data to obtain a corresponding output including predicted characteristics of the portion of particles after crushing the portion of particles with the crushing system; and adjusting parameters of the prediction model based on comparing the output of the prediction model to the post-crush particle data.


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