2 results about "Ground lift" patented technology

The invention relates to the technical field of vertical shaft construction, in particular to an SBE ground lifting system device which comprises a lifting bucket and a lifting rod, the lifting rod is movably connected to the top face of the lifting bucket, two arc-shaped shells are symmetrically arranged on the outer side wall of the lifting bucket, and two arc-shaped plates are symmetrically arranged between the two arc-shaped shells; the two sides of the arc-shaped plate are inserted into the arc-shaped shells on the two sides correspondingly, and the arc-shaped plate is movably connected with the arc-shaped shells. Through the arrangement of the arc-shaped shell, the arc-shaped plate, the fixed shell, the movable plate, the mounting assembly and the protection assembly, the arc-shaped shell and the arc-shaped plate can be firmly mounted on the hoisting bucket through the mounting assembly, and when the hoisting bucket is lifted through the bottom surface lifting system, the hoisting bucket is lifted through tight jacking between a plurality of rollers and the inner wall of the vertical shaft; and multi-point limiting of the hoisting bucket can be achieved, the hoisting stability of the hoisting bucket can be effectively improved, and hoisting use of the hoisting bucket is facilitated. The method has the advantages of being high in construction safety and good in universality.

This invention provides a method and system for identifying bipedal foot-to-ground contact states based on monocular video, relating to the field of data processing technology. The method includes: acquiring a two-dimensional keypoint sequence of human posture from monocular video; performing robust outlier suppression and smoothing differentiation on the two-dimensional keypoint sequence to obtain a smoothed keypoint coordinate and velocity sequence; extracting multiple kinematic features related to the bipedal foot-to-ground contact state; determining the estimated direction of human movement through a viewpoint adaptation mechanism, and projecting the foot velocity based on the direction of human movement to obtain viewpoint-adaptive velocity features; modeling the bipedal foot-to-ground contact state using an unsupervised two-component Gaussian mixture model and calculating the posterior probability that the feet are in the support phase; performing joint temporal decoding of the bipedal foot-to-ground contact state using a four-state coupled hidden Markov model and a Viterbi decoding algorithm to obtain a temporally consistent bipedal foot-to-ground contact state sequence; and completing the identification of the bipedal foot-to-ground contact state by extracting ground contact events and ground lift events.