Application of a Digital Signal Analyzer to the easurementTofF Power System Ground Impedances
A new method is described for measuring the impedance of power system ground systems where, because of a significant reactive component or the presence of a large residual power system voltage, conventional ground resistance measuring instruments cannot be used. A white noise source together with a digital signal analyzer are used. Results of three applications are given.
Digital Techniques in High-Voltage Measurements
A review of digital techniques and instruments developed and applied to high-voltage measurements is presented. Advantages of digital instruments over their analog homologues are exposed together with some examples of processing of digitized signals recorded in HV laboratories.
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.