wavelet analysis

The article focuses on innovative measurement and control methods in electrical power engineering, specifically addressing challenges of power quality, signal diagnostics, and automation within smart grids. Emphasis is placed on wavelet analysis, smart metering, IoT integration, and automated control systems. These technologies are examined in the context of enhancing the adaptability and efficiency of modern electrical systems in line with Industry 4.0 requirements.

The article examines modern approaches to the analysis of spread spectrum signals, particularly those based on pseudorandom frequency hopping and chirp spectrum expansion. The main focus is on the development and optimization of efficient time-frequency analysis methods for the identification and monitoring of such signals under real-world conditions, considering their complexity and dynamic nature.

In this work we propose method of aviation reduction drive diagnosis, which use Hilbert-Huang transform and wavelet analysis.