Fabricated self-resilient energy-dissipation double-steel-plate slotted shear wall structure

    公开(公告)号:US10895087B1

    公开(公告)日:2021-01-19

    申请号:US16624910

    申请日:2018-07-05

    Abstract: A fabricated self-resilient energy-dissipation double-steel-plate slotted shear wall structure includes steel columns, H-shaped steel beams and a shear wall assembly. The shear wall assembly includes left and right groups of slotted wall plates and is connected with flanges of the H-shaped steel beams through angle steel. Connecting ring plate assemblies are fixed to upper and lower ends of each steel column and each comprise an outer ring plate, an inner ring plate and a short side plate. A long side plate is fixedly arranged on each steel column tube and is connected with one slotted wall plate through a plurality of self-locking hasps. A plurality of pre-stressed steel strands are arranged on two sides of each long side plate.

    Translation-rotation hybrid vibration control system for buildings

    公开(公告)号:US10889982B2

    公开(公告)日:2021-01-12

    申请号:US16930281

    申请日:2020-07-15

    Abstract: There is provided a translation-rotation hybrid vibration control system for buildings, which includes a translation control unit and a rotation control unit. The translation control unit is provided on an external building structure. The rotation control unit is provided above the translation control unit. The translation control unit includes a fixed base, a first track plate, a first movable plate, a second track plate and a second movable plate. The rotation control unit includes a force-transfer base, a drive, a reducer, an output shaft, a rotary plate and a flange.

    ASSEMBLY MONITORING METHOD AND DEVICE BASED ON DEEP LEARNING, AND READABLE STORAGE MEDIUM

    公开(公告)号:US20200273177A1

    公开(公告)日:2020-08-27

    申请号:US16739115

    申请日:2020-01-10

    Abstract: The present invention relates to an assembly monitoring method based on deep learning, comprising steps of: creating a training set for a physical assembly body, the training set comprising a depth image set Di and a label image set Li of a 3D assembly body at multiple monitoring angles, wherein i represents an assembly step, the depth image set Di in the ith step corresponds to the label image set Li in the ith step, and in label images in the label image set Li, different parts of the 3D assembly body are rendered by different colors; training a deep learning network model by the training set; and obtaining, by the depth camera, a physical assembly body depth image C in a physical assembly scene, inputting the physical assembly body depth image C into the deep learning network model, and outputting a pixel segmentation image of the physical assembly body, in which different parts are represented by pixel colors to identify all the parts of the physical assembly body. In the present invention, parts in the assembly body can be identified, and the assembly steps, as well as the occurrence of assembly errors and the type of errors, can be monitored for the parts.

    NETWORKED CONTROL SYSTEM TIME-DELAY COMPENSATION METHOD BASED ON PREDICTIVE CONTROL

    公开(公告)号:US20200241487A1

    公开(公告)日:2020-07-30

    申请号:US16745581

    申请日:2020-01-17

    Abstract: The present invention discloses a networked control system (NCS) time-delay compensation method based on predictive control. The method comprises the following steps: (1) acquiring random time-delay data in an NCS, and preprocessing the data; (2) predicting the current time-delay by using a fuzzy neural network (FNN) optimized by a particle swarm optimization (PSO) algorithm; (3) compensating the predicted time-delay by using an implicit proportional-integral-based generalized predictive control (PIGPC) algorithm; (4) determining whether a preset work end time is up according to a clock in the NCS; if yes, ending the process; if no, returning to step (2). The method disclosed by the present invention can accurately predict and effectively compensate the NCS time-delay and has excellent development prospect.

    BUILDING CONSTRUCTION ROBOT
    126.
    发明申请

    公开(公告)号:US20250084652A1

    公开(公告)日:2025-03-13

    申请号:US18281513

    申请日:2023-05-17

    Abstract: A building construction robot is provided. The building construction robot includes a vehicle body, a feeding assembly is arranged in the vehicle body, a mounting frame is fixedly connected to one end of the vehicle body, and the mounting frame is located at a discharge end close to the feeding assembly. One end of a vibrating assembly is fixedly connected to one end of a top of the vehicle body, and the other end of the vibrating assembly passes through a middle part of the mounting frame. A leveling assembly is arranged at one end, away from the vehicle body, of the mounting frame, a measuring part is arranged at a top of the mounting frame, and a moving part is arranged at a bottom of the vehicle body.

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