Structural Health Diagnosis and Prognostics Using Fatique and Crack Growth Monitoring
Abstract
Fatigue damage sensing and crack propagation monitoring of any structure is a prerequisite for reliable and effective structural health monitoring. This paper, discusses the role of two different sensors, i.e., crack propagation (CP) and fatigue damage (FD) sensors in structural health monitoring. The CP sensor is capable of detecting crack initiation and subsequent propagation within the structural component that essentially constitutes a diagnostics approach. The FD sensor monitors the actual fatigue damage of the structural component and can be used for both diagnosis and prognosis of the remaining useful life. The CP sensor bonded to a structure at the critical location monitors the progression of a surface crack breaking through the successive strands, resulting in an increase in total resistance of the FD sensor having alternate slots and strips with different strain magnification factor with respect to the nominal strain at its location. The sensor is designed such that the strips experience the strains which closely resemble the actual strain distribution in the critical area of the component. One of the major advantages of this sensor is that it can be placed at any convenient location, still experiencing the same fatigue damage as a critical location. An interesting aspect of these sensors is that they are easily integrated with wireless networking, facilitating ease of use and real time data acquisition. Both sensors could be applied to various structures from ground civilian and military vehicles to steel bridges. This can predict the remaining useful life of a component or the number of miles (for any automobile) left for the component before it needed replacement.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 12, 2011
- Accession Number
- ADA541414
Entities
People
- Daniel Kujawski
- Muralidhar K. Ghantasala
- Shabbir Hussain
- Subash Gokanakonda
Organizations
- Western Michigan University