Ensuring life safety is the primary design and maintenance requirement for civil structures designed
to be serviceable for a specific lifetime. However, structures subjected to a number
of factors may experience quicker or more gradual deterioration than anticipated, or even a
premature loss of function. Scheduled visual inspection is the oldest and most commonly used
damage monitoring technique, but has significant disadvantages when quick damage assessment
and certainty are needed, such as after a major seismic event. Quick, accurate and quantitative
determination of the damage state is vital following an earthquake, to estimate damage, remaining
life-time, and ensure safe re-occupancy, if possible.
Rapid development of sensor technology and increasing computing power has enabled continuous
structural monitoring using various sensing techniques. The measured data can be analyzed
using structural health monitoring (SHM) methods. SHM refers to all elements of the
process of identifying mechanical properties of a structural system, comparing it with previous
states, detecting changes/abnormalities, and relating these to damage. A successful SHM
method should be able to automatically identify and locate damage after large, non-linear response
events.
The majority of existing, primarily vibration based, SHM techniques have serious limitations
in situations where a quick, accurate, and quantitative assessment is needed. More specifically,
many SHM techniques perform well when structures behave linearly and are subjected
to ambient loads, but this does not apply to earthquake events. Moreover, some methods can
only work off-line, involve significant computational effort and/or human input, and/or do not
provide any indication of damage location and/or severity.
To address these limitations, this thesis explores the application of a novel SHM implementation
strategy composed of a novel modal parameter identification and its subsequent application
to a proven hysteresis loop analysis (HLA) method. The study demonstrates the proposed
strategy can be readily used to track the performance of non-linear degrading structures subjected
to strong ground motion, essentially in real-time and without human input. Thus, the
proposed tools can be used to support/replace visual inspection results, reduce downtime, minimize
business disruptions and, most importantly, maximize life safety.
More specifically, this thesis proposes and analyses the application of a novel modal parameter
identification technique, which performs in near real-time and, most importantly, is efficient
when approximating non-linear structures subjected to relatively short duration ground motion
inputs. The technique operates in modal space and is based on a pre-defined optimization process,
which decouples frequency response spectra of interfering, generally higher frequency,
modes. Optimization can be realized over relatively short time windows to provide continuous
monitoring of highly non-linear, degrading structures.
In particular, identified modal parameters can be readily used to identify damage. However,
modal parameters can have very poor sensitivity to damage and are often difficult to interpret.
Thus, it is challenging to infer the location and severity of damage based on detected
changes/variation in modal parameters alone. In this research, the identified time-varying modal
parameters are used to decompose the structural response and reconstruct single mode dominant
restoring force-deformation hysteresis loops, which can be readily analyzed using recently
developed hysteresis loops analysis (HLA). The versatility and robustness of HLA has been
explored in a number of studies. However, the analyzed case structures employed in these validation
cases exhibited very small contribution from the higher modes, which typically can cause
significant irregularities, and make effective implementation of HLA more problematic. Hence,
this thesis aims to improve the robustness of HLA, using mode segregation and reconstruction
of single mode dominant, regular shape hysteresis loops from non-linear structural response.
First, this research develops a modal parameter output-only identification technique, which
is validated for a simple time-invariant linear structure. Second, the output-only method is extended
to an input-output method enabling operators to carry out near-real time identification of
non-linear structures, which is validated for a simple time-varying non-linear structure. Third,
the input-output method is validated using the simulation results of a more complex non-linear
multi-degree-of-freedom structure, formulated using fiber elements. Finally, the proposed SHM
strategy, consisting of continuous modal parameter identification and subsequent application of
HLA is validated for two experimental non-linear structures.
Overall, this thesis proposes a novel system identification technique, which performs outputonly
identification of linear structures and, more importantly, provides input-output real-time
modal parameter tracking of highly non-linear structures. Thus, the method extends the application
of modal SHM methods to non-linear cases. The proposed technique performs successfully
without operator input and can be easily automated to provide continuous modal tracking
and damage detection. The technique performs both as stand-alone for damage detection and in
combination with HLA for damage quantification as demonstrated for highly non-linear cases
