State Grid Corporation of China

State Grid Tianjin Electric Power Company

Electric Power Science & Research Institute of State Grid Tianjin Electric Power Company

Tcl Zhonghuan Renewable Energy Technology Co., Ltd.

Kun Wang

Chi Zhang

Wei Fan

Li Zhang

Guohao Li

Jian Wang

Jin He

Rong Chen

Zhibing Sun

Ziyue Wang

Jiafeng Lu

Liansheng Zhou

Junyou Zhang

Youyi Liu

Min Xiao

Jinxin Yan

Zhiyong Gan

Zhenyu Zhang

Duoduo Zhang

Bin Qu

Jinlu Shi

A surface flatness detecting device for single crystal square is provide. The device includes a clamping assembly and a detecting assembly. The clamping assembly has a first clamper and a second clamper, the first clamper and the second clamper are configured to clamp a first end and a second end of the single crystal square rod, respectively. The detecting assembly has a first detector and a second detector, the first detector and the second detector are configured to detect a first side and a second side of the single crystal square rod, respectively. After the first side and the second side are detected by the first detector and the second detector, respectively, the first clamper and the second clamper rotate the single crystal square rod by 90 degrees to detect a third side and a fourth side of the single crystal square rod.

Surface flatness detecting device for single crystal square rod

A GIS mechanical fault diagnosis method and the device are disclosed. The method includes: collecting vibration signals to be measured of various excitation sources of GIS in mechanical operation; performing wavelet packet-feature entropy vector extraction on the vibration signals to be measured, when it is determined that the vibration signals to be measured are abnormal according to standard vibration signals in the normal state; inputting the extracted wavelet packet-feature entropy vectors into the pre-trained BP neural network for GIS mechanical fault identification, and outputting the corresponding fault. The disclosure integrates the vibration signals under the action of various excitation sources, extracts the feature entropy vectors according to the entropy theory, and constructs and trains a BP neural network that can classify and recognize various GIS mechanical faults, so as to perform comprehensive and effective GIS mechanical faults diagnose.

GIS mechanical fault diagnosis method and device

Growing community of inventors

Tianjin, China

Kun Wang