3results about How to "Address sensitivity" patented technology

The invention relates to the technical field of intelligent evaluation of garment flatness, and particularly discloses an automatic evaluation method of a non-ironing suit seam flatness grade, and the method comprises the steps: obtaining image data and physical parameter data of a seam region in response to a detection trigger signal of the seam region of a non-ironing suit; and performing key scale screening based on texture contribution degree on the image data, calculating a relevance index between feature distribution and flatness grade probability distribution under different texture scales, and determining the texture scale of which the relevance index meets a preset contribution degree condition as a target key scale. According to the method, the entropy screening mechanism based on the texture contribution degree is introduced, so that the key scale which is most effective for flatness representation can be locked from the multi-source data in a self-adaptive manner, and the refinement and pertinence of feature extraction are realized.

The invention relates to a permanent magnet synchronous motor model prediction control method and system, belongs to the technical field of permanent magnet synchronous motor driving, and solves the problem that parameter robustness and dynamic performance cannot be considered when parameter mismatch occurs in permanent magnet synchronous motor model prediction control in the prior art. Comprising the steps of obtaining sampling values of stator current, stator voltage and electrical angular velocity at a current sampling moment and two previous moments and a direct current bus voltage at the current sampling moment, further updating incremental current prediction errors and time sequence sampling data of incremental voltage, and further obtaining a first sample vector and a second sample vector at the current sampling moment; and then a small-batch stochastic gradient descent method is adopted to obtain an identification value of a parameter mismatch coefficient at the current sampling moment, then stator current prediction values of different voltage vectors at the next moment are obtained, then an optimal voltage vector is obtained, and permanent magnet synchronous motor model prediction control at the next moment is carried out based on the optimal voltage vector.

This invention provides a lithium lanthanum zirconium oxide composite solid electrolyte, its preparation method, and its application, relating to the field of solid electrolyte technology. The lithium lanthanum zirconium oxide composite solid electrolyte comprises, from the inside out, a lithium lanthanum zirconium oxide core-shell particle layer, a chlorine-doped sulforaphane-germanium oxide electrolyte layer, and a PEO-LiTFSI-based flexible polymer electrolyte layer. The chlorine-doped sulforaphane-germanium oxide electrolyte in the chlorine-doped sulforaphane-germanium oxide electrolyte layer has the chemical formula Li. 7‑x PS 6‑x Cl x 0<x≤2, the room temperature ionic conductivity of the lithium lanthanum zirconium oxy-based composite solid electrolyte is 1.5 mS / cm, and the conductivity retention rate after 24 hours of air exposure is >90%.