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公开(公告)号：US20230020861A1
公开(公告)日：2023-01-19
申请号：US17374320
申请日：2021-07-13
Applicant: X Development LLC
Inventor： Allen Richard Zhao , Kenton Lee Prindle , Kevin Forsythe Smith , Artem Goncharuk
Abstract: This disclosure describes a system and method for generating images and location data of a subsurface object using existing infrastructure as a source. Many infrastructure objects (e.g., pipes, cables, conduits, wells, foundation structures) are constructed of rigid materials and have a known shape and location. Additionally these infrastructure objects can have exposed portions that are above or near the surface and readily accessible. A signal generator can be affixed to the exposed portion of the infrastructure object, which induces acoustic energy, or vibrations in the object. The object with affixed signal generator can then be used as a source in performing a subsurface imaging of subsurface objects, which are not exposed.
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公开(公告)号：US20210318465A1
公开(公告)日：2021-10-14
申请号：US17229391
申请日：2021-04-13
Applicant: X Development LLC
Inventor： Kenton Lee Prindle , Artem Goncharuk , Neil David Treat , Kevin Forsythe Smith , Thomas Peter Hunt , Karen R. Davis , Allen Richard Zhao
Abstract: This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale. Lithological attributes and characteristics present in available geoscience data can be correlated with related remote sensing data using a machine learning model, which can then infer lithological attributes and characteristics for regions where remote sensing data is available, but geoscience data is not.
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公开(公告)号：US20240165634A1
公开(公告)日：2024-05-23
申请号：US17990558
申请日：2022-11-18
Applicant: X Development LLC
Inventor： Ray Jr. Anthony Nagatani , Allen Richard Zhao , Antonio Raymond Papania-Davis , Weishi Yan , Brian Howell , Jeffrey Bush , Charles Stephen Spirakis
CPC classification number: B02C25/00 , G05B13/027 , G05B13/042
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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公开(公告)号：US11835560B2
公开(公告)日：2023-12-05
申请号：US18160651
申请日：2023-01-27
Applicant: X Development LLC
Inventor： Alex S. Miller , Artem Goncharuk , Allen Richard Zhao , Kevin Forsythe Smith
IPC: H01H31/02 , G01R29/08 , G01R27/28 , G01R31/08 , G01R31/52 , G01R31/58 , G01R1/067 , H04M1/24 , H04M3/28 , H04M3/30
CPC classification number: G01R29/0842 , G01R1/06788 , G01R27/28 , G01R29/0878 , G01R31/085 , G01R31/52 , G01R31/58 , H04M1/24 , H04M3/28 , H04M3/30
Abstract: This disclosure describes a system and method for generating images by performing TEM surveys using pre-existing infrastructure such as transmission lines, or power lines, and naturally occurring transients such as lightning strikes or load switching. A relatively inexpensive sensor array can be installed on overhead power lines (e.g., electrical transmission or sub-transmission lines) which can detect transients in the overhead power lines. Transients in the overhead power lines can cause the power lines to emit pulses of electromagnetic (EM) radiation, which propagate into the earth's subsurface. This sudden change in electromagnetic field in the subsurface can induce eddy currents, which in turn emit return EM radiation that can propagate back to the overhead power line and induce secondary voltage and current transients. The magnitude of these secondary transients, and their time delay from the original transient are influenced by the properties of the subsurface in which the eddy currents formed.
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公开(公告)号：US11774614B2
公开(公告)日：2023-10-03
申请号：US17374320
申请日：2021-07-13
Applicant: X Development LLC
Inventor： Allen Richard Zhao , Kenton Lee Prindle , Kevin Forsythe Smith , Artem Goncharuk
CPC classification number: G01V1/30 , G01V1/18 , G01V2210/121 , G01V2210/1295 , G01V2210/1425 , G01V2210/66
Abstract: This disclosure describes a system and method for generating images and location data of a subsurface object using existing infrastructure as a source. Many infrastructure objects (e.g., pipes, cables, conduits, wells, foundation structures) are constructed of rigid materials and have a known shape and location. Additionally these infrastructure objects can have exposed portions that are above or near the surface and readily accessible. A signal generator can be affixed to the exposed portion of the infrastructure object, which induces acoustic energy, or vibrations in the object. The object with affixed signal generator can then be used as a source in performing a subsurface imaging of subsurface objects, which are not exposed.
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Patent Agency Ranking
公开(公告)号：US11606507B1
公开(公告)日：2023-03-14
申请号：US17005735
申请日：2020-08-28
Applicant: X Development LLC
Inventor： Allen Richard Zhao , Jerome Nowak , Benoit Schillings
Abstract: A system and method for automated lens adjustment for hyperspectral imaging is described. The system includes an image sensor and an electrically-controllable element arranged to set a spectral band for image capture by (i) selectively providing light for a selected spectral band or (ii) selectively filtering light to a selected spectral band. The system includes a tunable lens that is adjustable to change a focal length of the lens; and one or more data storage devices storing data that indicates different focus adjustment parameters corresponding to different spectral bands. The system includes a control system configured to perform operations including: selecting a spectral band; controlling the electrically-controllable element to set the spectral band for image capture; retrieving the focus adjustment parameter that corresponds to the spectral band; adjusting the lens based on the retrieved focus adjustment parameter; and capturing an image of the subject while the lens remains adjusted.
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公开(公告)号：US11592594B2
公开(公告)日：2023-02-28
申请号：US17229391
申请日：2021-04-13
Applicant: X Development LLC
Inventor： Kenton Lee Prindle , Artem Goncharuk , Neil David Treat , Kevin Forsythe Smith , Thomas Peter Hunt , Karen R Davis , Allen Richard Zhao
Abstract: This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale. Lithological attributes and characteristics present in available geoscience data can be correlated with related remote sensing data using a machine learning model, which can then infer lithological attributes and characteristics for regions where remote sensing data is available, but geoscience data is not.
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公开(公告)号：US20230027514A1
公开(公告)日：2023-01-26
申请号：US17383293
申请日：2021-07-22
Applicant: X Development LLC
Inventor： Hongxu Ma , Allen Richard Zhao , Cyrus Behroozi , Derek Werdenberg , Jie Jacquot , Vadim Tschernezki
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for image segmentation and chemical analysis using machine learning. In some implementations, a system obtains a hyperspectral image that includes a representation of an object. The system segments the hyperspectral image to identify regions of a particular type on the object. The system generates a set of feature values derived from image data for different wavelength bands that is located in the hyperspectral image in the identified regions of the particular type. The system generates a prediction of a level of one or more chemicals in the object based on an output produced by a machine learning model in response to the set of feature values being provided as input to the machine learning model. The system provides data indicating the prediction of the level of the one or more chemicals in the object.
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公开(公告)号：USD956840S1
公开(公告)日：2022-07-05
申请号：US29694998
申请日：2019-06-14
Applicant: X Development LLC
Designer： Derek Werdenberg , Allen Richard Zhao , Phillip Yee , Joseph Hollis Sargent
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公开(公告)号：US12033329B2
公开(公告)日：2024-07-09
申请号：US17383278
申请日：2021-07-22
Applicant: X Development LLC
Inventor： Hongxu Ma , Allen Richard Zhao , Cyrus Behroozi , Derek Werdenberg , Jie Jacquot , Vadim Tschernezki
CPC classification number: G06T7/11 , G06V10/26 , G06T2207/10036 , G06T2207/20224
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improved image segmentation using hyperspectral imaging. In some implementations, a system obtains image data of a hyperspectral image, the image data comprising image data for each of multiple wavelength bands. The system accesses stored segmentation profile data for a particular object type that indicates a predetermined subset of the wavelength bands designated for segmenting different region types for images of an object of the particular object type. The system segments the image data into multiple regions using the predetermined subset of the wavelength bands specified in the stored segmentation profile data to segment the different region types. The system provides output data indicating the multiple regions and the respective region types of the multiple regions.
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