Vibration-based damage detection (VBDD) methods are structural health monitoring techniques that utilize changes to the dynamic characteristics of a structure (i.e. its natural frequencies, mode shapes, and damping properties) as indicators of damage. While conceptually simple, considerable research is still required before VBDD methods can be applied reliably to complex structures such as bridges. VBDD methods require reliable estimates of modal parameters (notably natural frequencies and mode shapes) in order to assess changes in the condition of a structure. This thesis presents the results of experimental and numerical studies investigating a number of issues related to the potential use of VBDD techniques in the structural health monitoring of bridges, the primary issue being the influence of the excitation source.<p> Two bridges were investigated as part of this study. One is located on Provincial Highway No. 9 over the Red Deer River south of Hudson Bay, Saskatchewan. The other is located near the Town of Broadview, Saskatchewan, off Trans-Canada Highway No. 1, 150 km east of the City of Regina. Field tests and numerical simulations were conducted using different types of excitation to evaluate the quality of the modal properties (natural frequencies and mode shapes) calculated using these excitation types, and thus to evaluate the performance of VBDD techniques implemented using the resulting modal data. Field tests were conducted using different sources of dynamic excitation: ambient, traffic excitation, and impact excitation. The purpose of field testing was to study the characteristics and repeatability of the modal parameters derived using the different types of dynamic excitation, and to acquire data that could be used to update a FE model for further numerical simulation.<p> A FE model of the Red Deer River bridge, calibrated to match the field measured dynamic properties, was subjected to different types of numerically simulated dynamic excitation with different noise (random variations) levels added to them. The types of dynamic excitation considered included harmonic forced excitation, random forced excitation and the subsequent free vibration decay, impact excitation, and different models of truck excitation. The bridge model was subjected to four different damage scenarios; in addition, six VBDD methods were implemented to evaluate their ability to identify and localize damage. The effects of uncertainty in the definition of controlled-force excitation sources and variation in measurement of the bridge response were also investigated.<p> Field tests on the Hudson Bay bridge showed that excitation induced by large trucks generally produced more reliable data than that of smaller vehicles due to higher signal-to-noise ratios in the measured response. It was also found that considering only the free vibration phase of the response after the vehicle left the bridge gave more reliable data. Impact excitation implemented the on Hudson Bay bridge using a spring-hammer yielded repeatable and high quality results, while using a heavy weight delectometer for impact excitation on the Broadview bridge produced results of lesser quality due to the occurrence of multiple strikes of the impact hammer. In general, wind induced vibration measurements taken from both bridges were less effective for defining modal properties than large vehicle loading or impact excitation. All of the VBDD methods examined in this study could detect damage if the comparison was made between modal parameters acquired by eigenvalue analyses of two FE models of the bridge, before and after damage. However, the performance of VBDD methods declined when the dynamic properties were calculated from response time histories and noise was introduced. In general, the damage index method performed better than other damage detection methods considered.<p> Numerical simulation results showed that harmonic excitation, impact excitation, and the free decay phase after random excitation yielded results that were consistent enough to be used for the identification of damage. The reliability of VBDD methods in detecting damage dropped once noise was introduced. Noise superimposed on the excitation force had little effect on the estimated modal properties and the performance of VBDD methods. On the other hand, noise superimposed on the measured dynamic response had a pronounced negative influence on the performance of the VBDD methods.

Vibration-based damage detection (VBDD) methods are structural health monitoring techniques that utilize changes to the dynamic characteristics of a structure (i.e. its natural frequencies, mode shapes, and damping properties) as indicators of damage. While conceptually simple, considerable research is still required before VBDD methods can be applied reliably to complex structures such as bridges. VBDD methods require reliable estimates of modal parameters (notably natural frequencies and mode shapes) in order to assess changes in the condition of a structure. This thesis presents the results of experimental and numerical studies investigating a number of issues related to the potential use of VBDD techniques in the structural health monitoring of bridges, the primary issue being the influence of the excitation source.<p> Two bridges were investigated as part of this study. One is located on Provincial Highway No. 9 over the Red Deer River south of Hudson Bay, Saskatchewan. The other is located near the Town of Broadview, Saskatchewan, off Trans-Canada Highway No. 1, 150 km east of the City of Regina. Field tests and numerical simulations were conducted using different types of excitation to evaluate the quality of the modal properties (natural frequencies and mode shapes) calculated using these excitation types, and thus to evaluate the performance of VBDD techniques implemented using the resulting modal data. Field tests were conducted using different sources of dynamic excitation: ambient, traffic excitation, and impact excitation. The purpose of field testing was to study the characteristics and repeatability of the modal parameters derived using the different types of dynamic excitation, and to acquire data that could be used to update a FE model for further numerical simulation.<p> A FE model of the Red Deer River bridge, calibrated to match the field measured dynamic properties, was subjected to different types of numerically simulated dynamic excitation with different noise (random variations) levels added to them. The types of dynamic excitation considered included harmonic forced excitation, random forced excitation and the subsequent free vibration decay, impact excitation, and different models of truck excitation. The bridge model was subjected to four different damage scenarios; in addition, six VBDD methods were implemented to evaluate their ability to identify and localize damage. The effects of uncertainty in the definition of controlled-force excitation sources and variation in measurement of the bridge response were also investigated.<p> Field tests on the Hudson Bay bridge showed that excitation induced by large trucks generally produced more reliable data than that of smaller vehicles due to higher signal-to-noise ratios in the measured response. It was also found that considering only the free vibration phase of the response after the vehicle left the bridge gave more reliable data. Impact excitation implemented the on Hudson Bay bridge using a spring-hammer yielded repeatable and high quality results, while using a heavy weight delectometer for impact excitation on the Broadview bridge produced results of lesser quality due to the occurrence of multiple strikes of the impact hammer. In general, wind induced vibration measurements taken from both bridges were less effective for defining modal properties than large vehicle loading or impact excitation. All of the VBDD methods examined in this study could detect damage if the comparison was made between modal parameters acquired by eigenvalue analyses of two FE models of the bridge, before and after damage. However, the performance of VBDD methods declined when the dynamic properties were calculated from response time histories and noise was introduced. In general, the damage index method performed better than other damage detection methods considered.<p> Numerical simulation results showed that harmonic excitation, impact excitation, and the free decay phase after random excitation yielded results that were consistent enough to be used for the identification of damage. The reliability of VBDD methods in detecting damage dropped once noise was introduced. Noise superimposed on the excitation force had little effect on the estimated modal properties and the performance of VBDD methods. On the other hand, noise superimposed on the measured dynamic response had a pronounced negative influence on the performance of the VBDD methods.

Ageing mechanical, civil, aerospace, marine and offshore structures require continuous and accurate assessment on their integrity to avoid potentially hazardous failures. To further facilitate this crucial demand, a new technical terminology, generally referred to as structural health monitoring (SHM) has been coined in three past decades. SHM involves deployment of a sensory network on such structures in order to gather useful data, such that processing and interpreting the data through specific algorithms would enable one to detect defects and anomalies within the structures. This dissertation presents the results of a series of efforts expended towards the refinement and enhancement of a vibration-based SHM technique, which was originated within our research group. In the adopted damage detection scheme, vibration data are gathered from structures via piezoelectric sensors. Data are processed by a robust signal processing approach, known as the empirical mode decomposition (EMD) in order to establish energy-based damage indices (EMD_EDIs). Interpretation of the damage indices enables detection of onset, location and advancement of defects within structures. A series of adjustments and modifications were devised and implemented to the application of the originally developed methodology, such that, besides increasing the methodology’s robustness and accuracy, they also facilitate a remote vibration-based SHM targeting onshore and offshore pipelines. The integrity of the method in detection of bolt-loosening in a bolted flange joint of a full-scale pipeline was verified through numerical simulations and experimental investigations. The source of a significant inconsistency reported in the previous trials was identified and resolved. Also, for the first time, the remote application of the technique was facilitated by incorporating an advanced wireless data acquisition system. Moreover, the application of the methodology was extended to detection of cracks in girth-welds of offshore pipelines. In this regard, a comprehensive discussion is first provided, which identifies the role of parameters that influence the accuracy of numerical modeling of the dynamic response of submerged structures. The experimental and numerical investigation following the aforementioned modeling efforts presents encouraging results in detection of an advancing notch in the girth-weld of a submerged pipe. The use of a piezoelectric-based excitation technique, incorporated for the first time in the application of the methodology would evidence the enhanced practicality and robustness of the approach. The study concludes with a successful detection of a real-life sharp propagating crack in a beam due to cyclic loadings.

A vibration-based sound power (VBSP) measurement method is appealing because of its potential versatility in application compared to pressure- and intensity-based methods. The VBSP method is based on the well-known elementary radiators approach and is reliant on the acoustic radiation resistance matrix. Previous research has developed and validated the VBSP method for flat plates and cylinders. This thesis details work on extending the VBSP method to arbitrarily-curved structures. The approach of computing surface normal velocities from 3D velocity data measured by a scanning laser Doppler vibrometer (SLDV) is presented. This approach is validated with experimental sound power results of a cylindrical shell using the VBSP method with 3D velocity and geometry data. The sound power results are shown to have good agreement with ISO 3741 results. Experimental sound power results from three simple-curved plates using the VBSP and ISO 3741 methods are shown to have good agreement. These experimental results indicate that the VBSP method is less sensitive to background noise than the ISO 3741 method. An overview of exploring inherent symmetry in the radiation resistance matrix is presented for the purpose of increasing efficiency in applying the VBSP method. Sound power sensitivity to the formulation of the radiation resistance matrix is explored as another relevant option for increasing the efficiency of the VBSP method for many cases and for extending the method to more complex structures. The results of the radiation resistance matrix exploration enable the VBSP method to apply to arbitrarily-curved structures. Experimental sound power results using the VBSP method with the simple-curved plate radiation resistance matrix and the ISO 3741 method are compared for two arbitrarily-curved panels and are shown to have good agreement. The VBSP method based on the simple-curved plate form of the radiation resistance matrix is shown to have excellent agreement with numerical results from boundary element models, which inherently use the appropriate form of the radiation resistance matrix.

There is a need to monitor the existence and effects of damage in structural materials. Aircraft components provide a much publicized example, but the need exists in a variety of other structures, such as layered materials used in food packaging industries. While several techniques and models have been proposed for material characterization and condition monitoring of bulk materials, less attention has been devoted to thin sheets having no flexural rigidity. This study is therefore devoted to the development of a new method for acoustic Non-Destructive Testing (NDT) and material characterization of thin sheets used in food packaging materials or similar structures. A method for assessing the strength in the presence of crack of thin sheets used in food packaging is first presented using a modified Strip Yield Model (SYM). Resonance frequency measurement is then introduced and it is shown, at low frequency range (less than 2kHz), that a change in the physical properties such as a reduction in stiffness resulting from the onset of cracks or loosening of a connection causes detectable changes in the modal properties, specifically the resonance frequency. This observation leads to the implementation of a simple method for damage severity assessment on sheet materials, supported by a new theory illustrating the feasibility of the detection of inhomogeneity in form of added mass, as well as damage severity assessment, using a measurement of the frequency shift. A relationship is then established between the resonance frequency and the material’s elastic property, which yields a new modality for sheet materials remote characterization. The result of this study is the groundwork of a low-frequency vibration-based method with remote acoustic excitation and laser detection, for nondestructive testing and material characterization of sheet materials. The work also enhances the feasibility of the testing and condition monitoring of real structures in their operating environment, rather than laboratory tests of representative structures. The sensitivity of the new experimental approach used is liable to improvement while being high because the frequency measurement is one of the most accurate measurements in physics and metrology.

In a wide range of industries, machine condition monitoring is one of the most cost effective ways to minimise maintenance efforts and machine downtime. To implement such a system, wireless solutions have increasingly become an attractive proposition due to the ease of installation and minimal infrastructure alternation. However, currently most wireless sensors in the world are powered by a finite battery source. The dependence of batteries not only requires frequent maintenance, but also has adverse environmental consequences associated with battery disposal. These reasons render massive deployment of wireless sensors in the industry problematic. With the advances in semiconductors, power consumption of wireless sensors has been continuously decreasing. It is an inevitable trend for self-powered wireless sensors to emerge and become the norm for machine and environmental monitoring. In this research, vibration is chosen to be the energy source to enable self-powered wireless sensors due to its ubiquitousness in machinery and industrial environments. As a result of relying on resonance, the biggest challenge for vibration-based energy harvesters is their narrow bandwidth. Even a small deviation of the vibration frequency can dramatically reduce the power output. The primary goal of this research is to address this problem. In particular, Piezoelectric generators are identified to be the most suitable technology. In this work, extensive theoretical and experimental studies are conducted in single mass and multi-modal harvesters, and in resonance tuning harvesters by modulus and impedance matching as well as by mechanical actuation. Mathematical modelling plays a significant role in energy harvester designs. A dynamic model that generalises the single degree of freedom models and the continuum models is derived and validated by experiments. The model serves as the building block for the whole research, and it is further refined for the investigation of modulus and impedance matching. In the study of multi-modal harvesters, a continuum model for double-mass piezoelectric cantilever beams is derived and experimentally validated. To study the feasibility of resonance tuning by mechanical means, prototypes were built and performance evaluated. This document details the theoretical basis, concepts and experimental results that extend the current knowledge in the field of energy harvesting. This research work, being highly industrially focused, is believed to be a very significant step forward to a commercial energy harvester that works for a wide range of vibration frequencies.

Master of Science / Department of Civil Engineering / Hani G. Melhem / This study reports the results of an analytical, experimental and a numerical study (proof of concept study) on a proposed method for extracting the pseudo-free-vibration response of a structure using ambient vibration, usually of a random nature, as a source of excitation to detect any change in the dynamic properties of a structure that may be caused by damage. The structural response contains not only a random component but also a component reflecting the dynamic properties of the structure, comparable to the free vibration for a given initial condition. Structural response to the arbitrary excitation is recorded by one or several accelerometers with a desired data-collection frequency and resolution. The free-vibration response of the structure is then extracted from this data by removing the random component of the response by the method proposed in this study. The features of the free-vibration response of the structure extracted by a suitable method, namely Fast Fourier Transform (FFT) in this study, can be used for change detection. Possible change of the pattern of these features is dominantly linked to the change in dynamic properties of the system, caused by possible damage. To show the applicability of the concept, besides an analytical verification using Newmark’s linear acceleration method, two steel portal frames with different flexural stiffness were made in the steel workshop of the structural laboratory for an experimental study. These structures were also numerically modeled using a finite element software. A wireless accelerometer with a sampling frequency rate of 2046 Hz was affixed on the top of the physical structure, at the same location where the acceleration was recorded for the corresponding numerical model. The physical structure was excited manually by an arbitrary hit and the response of the structure to this excitation, in terms of the acceleration on the top of the structure, was recorded. The pseudo-free-vibration response was extracted and transferred into frequency domain using FFT. The frequency with the largest magnitude which is the fundamental frequency of the structure was traced. This was repeated for several independent excitations and the fundamental frequencies were observed to be the same, showing that the process can correctly identify the natural frequencies of the structure. Similarly, the numerical model was excited and for several base excitation cases, the fundamental frequencies were found to be the same. Considering the acceptable accuracy of the results from the two numerical models in simulating the response of their corresponding physical models, additional numerical models were analyzed to show the consistency and applicability of the proposed method for a range of flexural stiffness and damping ratio. The results confirm that the proposed method can precisely extract the pseudo-free-vibration response of the structures and detect the structural frequencies regardless of the excitation. The fundamental frequency is tied to the stiffness and a larger stiffness leads to a higher frequency, as expected, regardless of the simulated ambient excitation.

Vibration-based damage detection (VBDD) comprises a family of non-destructive testing methods in which changes to dynamic characteristics are used to track the condition of a structure. Although VBDD methods have been successfully applied to various mechanical systems and to simple beam-like structures, significant challenges remain in extending this technology to complex, spatially distributed structures such as bridges. <p> In the present study, numerical simulations using a calibrated finite element model were used to investigate the use of VBDD methods to detect small-scale damage on a two-span, integral abutment overpass structure located in Saskatoon, Saskatchewan. The small scale damage was defined in this study as the removal of a concrete element from the top surface of the bridge deck, resembling the spalled clear cover of concrete deck of the overpass. Five different VBDD techniques were evaluated, including the Change in Mode Shape, Change in Flexibility, Change in Mode Shape Curvature, Change in Uniform Flexibility Curvature and Damage index methods. In addition, the influence of the size of damage, the orientation of damage geometry, sensor spacing (3 m, 5 m and 7.5 m), the approach used for mode shape normalization, and uncertainty in the measured mode shapes was investigated. <p> It was found that localized damage could be reliably detected and located if the sensors were located within 3 m of the damage (the distance between adjacent girders) and if uncertainty in the mode shapes was attenuated through the use of a sufficient number of repeated trials. Furthermore, studies using a limited sensor installation that could be achieved without interrupting the flow of traffic indicated that small scale damage could be detected and potentially located using sensors that are placed well away from the damaged area, provided uncertainty in mode shape was attenuated.

Vibration-based damage detection (VBDD) comprises a family of non-destructive testing methods in which changes to dynamic characteristics are used to track the condition of a structure. Although VBDD methods have been successfully applied to various mechanical systems and to simple beam-like structures, significant challenges remain in extending this technology to complex, spatially distributed structures such as bridges. <p> In the present study, numerical simulations using a calibrated finite element model were used to investigate the use of VBDD methods to detect small-scale damage on a two-span, integral abutment overpass structure located in Saskatoon, Saskatchewan. The small scale damage was defined in this study as the removal of a concrete element from the top surface of the bridge deck, resembling the spalled clear cover of concrete deck of the overpass. Five different VBDD techniques were evaluated, including the Change in Mode Shape, Change in Flexibility, Change in Mode Shape Curvature, Change in Uniform Flexibility Curvature and Damage index methods. In addition, the influence of the size of damage, the orientation of damage geometry, sensor spacing (3 m, 5 m and 7.5 m), the approach used for mode shape normalization, and uncertainty in the measured mode shapes was investigated. <p> It was found that localized damage could be reliably detected and located if the sensors were located within 3 m of the damage (the distance between adjacent girders) and if uncertainty in the mode shapes was attenuated through the use of a sufficient number of repeated trials. Furthermore, studies using a limited sensor installation that could be achieved without interrupting the flow of traffic indicated that small scale damage could be detected and potentially located using sensors that are placed well away from the damaged area, provided uncertainty in mode shape was attenuated.

Structural Health Monitoring (SHM) is an effective alternative to conventional inspections which are time-consuming and subjective. SHM can detect damage early and reduce maintenance cost and thereby help reduce the likelihood of catastrophic structural events to infrastructure such as bridges. After reviewing the Damage Index Method, an Iterative Damage Index Method (IDIM) is proposed to improve the accuracy of damage detection. These two damage detection techniques are compared numerically and experimentally using measurements from two structures, a simply supported beam and a pedestrian bridge. The dynamic properties for the numerical comparison are extracted by modal analysis in ABAQUS, while the dynamic characteristics for the experimental comparison are obtained with the Wireless Sensor Network and the Time Domain Decomposition. In both the numerical and experimental phases, the accuracy of damage predictions from each method is quantified. Compared to the traditional damage detection algorithm, the proposed IDIM is shown to be less arbitrary and more accurate when applied to both structures. The proposed IDIM has the potential to improve SHM.