Jinlong Zhao

Research Field

The method of insulator recognition based on deep learning

Yue Liu Jun Yong Liang Liu Jinlong Zhao Zongyu Li

The insulator is an import part of transmission line, and the defects detection of insulator rely deeply on the insulators' position. Traditional methods about insulator recognition task are depend on color features and geometric features, those methods would be influenced by lots of factors, such as illumination and background in result getting poor generalization ability. In this paper, we propose a method to recognize insulator based on deep learning algorithm. Firstly, we construct the training dataset which includes insulator, background and tower three categories. Secondly, we initialize the convolution neural networks as a six-level network, and adjust training parameters to train the model. Lastly, the trained model is used to predict the candidate insulator position. With the help of non-maximum suppression algorithm and line fitting method, we can get the exactly location of insulator. The experiment results on UAV dataset show the proposed method can effective localize the insulator and improve generalization ability significantly.

10.1109/carpi.2016.7745630

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Citations (33)

Development and Application of Partial Discharge Detection Robot in Switchgear

Yiqing Luan Haipeng Wang Wei Xu Dazhou Zhou Jinlong Zhao

The partial discharge detection of switchgear can only depend on manual operation at present, and there exist many problems such as large workload, low detection efficiency and poor detection quality. This paper proposed a robot for partial discharge detection of switchgears can solve those above-mentioned problems. Based on the actual problems in the field, the device is developed, meanwhile the article discussed the design of the robot overall scheme, function and key technology of each module in detail, finally applied to field test. It has significance of engineering practice.

Switchgear

10.1109/iaeac.2018.8577851

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Citations (1)

Two-Step Gradient Reduction of Zirconia for Making High-Purity Zirconium Powder

JOM (2019)

Yang Xia Jinlong Zhao Zhaowang Dong Xueyi Guo Qinghua Tian

Metal powder

Particle (ecology)

Iron powder

10.1007/s11837-019-03958-y

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