[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7779/JKSNT.2016.36.2.93

Analysis of Time Domain Active Sensing Data from CX-100 Wind Turbine Blade Fatigue Tests for Damage Assessment

Choi, Mijin (Department of Aerospace Engineering & LANL-CBNU Engineering Institute, Chunbuk National University)
Jung, Hwee Kwon (School of Mechanical Engineering, Chonnam National University)
Taylor, Stuart G. (The Engineering Institute, Los Alamos National Laboratory)
Farinholt, Kevin M. (The Engineering Institute, Los Alamos National Laboratory)
Lee, Jung-Ryul (Department of Aerospace Engineering, KAIST)
Park, Gyuhae (School of Mechanical Engineering, Chonnam National University)

Publication Information

Journal of the Korean Society for Nondestructive Testing / v.36, no.2, 2016 , pp. 93-101 More about this Journal

Abstract

This paper presents the results obtained using time-series-based methods for structural damage assessment. The methods are applied to a wind turbine blade structure subjected to fatigue loads. A 9 m CX-100 (carbon experimental 100 kW) blade is harmonically excited at its first natural frequency to introduce a failure mode. Consequently, a through-thickness fatigue crack is visually identified at 8.5 million cycles. The time domain data from the piezoelectric active-sensing techniques are measured during the fatigue loadings and used to detect incipient damage. The damage-sensitive features, such as the first four moments and a normality indicator, are extracted from the time domain data. Time series autoregressive models with exogenous inputs are also implemented. These features could efficiently detect a fatigue crack and are less sensitive to operational variations than the other methods.

Keywords

Structural Health Monitoring (SHM); Time Series Analysis; Piezoelectric Active Sensor; ARX Model;

Citations & Related Records

Reference

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