Identification of multiple damage in beams based on robust curvature mode shapes

Multiple damage identification in beams using curvature mode shape has become a research focus of increasing interest during the last few years. On this topic, most existing studies address the sensitivity of curvature mode shape to multiple damage. A noticeable deficiency of curvature mode shape, however, is its susceptibility to measurement noise, easily impairing its advantage of sensitivity to multiple damage. To overcome this drawback, the synergy between a wavelet transform (WT) and a Teager energy operator (TEO) is explored, with the aim of ameliorating the curvature mode shape. The improved curvature mode shape, termed the TEO-WT curvature mode shape, has inherent capabilities of immunity to noise and sensitivity to multiple damage. The efficacy of the TEO-WT curvature mode shape is analytically verified by identifying multiple cracks in cantilever beams, with particular emphasis on its ability to locate multiple damage in noisy conditions; the applicability of the proposed curvature mode shape is experimentally validated by detecting multiple fairly thin slots in steel beams with mode shapes acquired by a scanning laser vibrometer. The proposed curvature mode shape appears sensitive to multiple damage and robust against noise, and therefore is well suited to identification of multiple damage in beams in noisy environments.