Fault Identification in Membrane Structures Using the Hilbert Transforms.

Area of Science:

• Engineering
• Materials Science
• Structural Health Monitoring

Background:

• Fault diagnostics are critical for machine condition monitoring and structural health.
• Early fault identification significantly impacts the safety of monitored structures.
• Timely detection enables monitoring fault progression and selecting optimal operational strategies.

Purpose of the Study:

• To present a novel method for structural health monitoring.
• To detect and analyze fault formations and their development in membrane structures.
• To utilize Hilbert transforms for enhanced fault detection capabilities.

Main Methods:

• Application of Hilbert transforms, specifically the Generalized Hilbert Transform (GHT) and the Fractional Hilbert Transform (FrHT).
• Analysis of signals generated by Hilbert transforms.
• Utilizing spectral analysis to identify fault indicators within the signals.

Main Results:

• The proposed method effectively detects fault formations in membrane structures.
• The Hilbert transform-based approach allows for monitoring the development of faults over time.
• Spectral analysis of HT signals reveals key features indicative of the structure's technical state.

Conclusions:

• The Hilbert transform-based method provides a robust approach for structural health monitoring.
• This technique aids in the early detection and tracking of faults in membrane structures.
• The findings contribute to improved safety and operational management of critical infrastructure.