Self-healing materials have received considerable development in the last decade. Recent results have demonstrated healing in polymeric materials via a chemical reaction using a healing agent or response to thermal treatment. The goal of this research is to develop a new composite material, for application in wire insulation, that can detect damage and heal itself using resistance heating. The composite material is composed of a conductive network embedded in a polymer matrix. The conductive network is used for damage detection and resistive heating. A matrix material is used that melts when heated and flows to fill damage. External electronic circuitry is used to implement a damage detection algorithm and apply current for resistive heating. Surlyn 8940 is chosen as the polymer matrix and carbon fibers are selected for the resistive heating elements. Methods for melt processing Surlyn are developed and used to produce Surlyn films and composite samples where carbon fiber is embedded in a Surlyn matrix. A finite element model of the resistive heating process is developed to predict the temperature distribution. Thermal imaging is used to characterize resistive heating while optical microscopy and tensile testing are used to characterize healing. Damage detection using capacitive measurements is demonstrated and characterized. The self-healing composite is placed on top of another conductive material such as in the wire insulation application. Capacitance measurements are made using the conductive network inside the composite is used as one electrode and the wide conductor as the second electrode. / Master of Science

No description available.

This research investigates the performance of an existing structural damage detection method (SDIM) when only experimentally-obtained measurement information can be used to calculate the frequency response functions used to detect damage. The development of a SDIM that can accurately identify damage while processing measurements containing realistic noise levels and overcoming experimental modeling errors would provide a robust method for identifying damage in the larger, more complex structures found in practice. The existing SDIM program, GaDamDet, uses an advanced genetic algorithm, along with a two-dimensional finite element model of the structure, to identify the location and the severity of damage using the linear vibration information contained in frequency response functions (FRF) as response signatures. Datagen is a Matlab program that simulates the three-dimensional dynamic response of the four-story, two-bay by two-bay UBC test structure built at the University of British Columbia. The dynamic response of the structure can be obtained for a range of preset damage cases or for any user-defined damage case. Datagen can be used to provide the FRF measurement information for the three-dimensional test structure. Therefore, using the FRF measurements obtained from the UBC test structure allows for a more realistic evaluation of the performance of the SDIM provided by GaDamDet as the impact on performance of more realistic noise and model errors can be investigated. Previous studies evaluated the performance of the SDIM using only simulated FRF measurements obtained from a two-dimensional structural model. In addition, the disparity between the two-dimensional model used by the SDIM used to identify damage and the measurements obtained from the three-dimensional test structure is analyzed. The research results indicate that the SDIM is able to accurately detect structural damage to individually damaged members or to within a damaged floor, with few false damages identified. The SDIM provides an easy to use, visual, and accurate algorithm and its performance compares favorably to performance of the various damage detection algorithms that have been proposed by researchers to detect damage in the three-dimensional structural benchmark problem.

This research investigates the performance of an existing structural damage detection method (SDIM) when only experimentally-obtained measurement information can be used to calculate the frequency response functions used to detect damage. The development of a SDIM that can accurately identify damage while processing measurements containing realistic noise levels and overcoming experimental modeling errors would provide a robust method for identifying damage in the larger, more complex structures found in practice. The existing SDIM program, GaDamDet, uses an advanced genetic algorithm, along with a two-dimensional finite element model of the structure, to identify the location and the severity of damage using the linear vibration information contained in frequency response functions (FRF) as response signatures. Datagen is a Matlab program that simulates the three-dimensional dynamic response of the four-story, two-bay by two-bay UBC test structure built at the University of British Columbia. The dynamic response of the structure can be obtained for a range of preset damage cases or for any user-defined damage case. Datagen can be used to provide the FRF measurement information for the three-dimensional test structure. Therefore, using the FRF measurements obtained from the UBC test structure allows for a more realistic evaluation of the performance of the SDIM provided by GaDamDet as the impact on performance of more realistic noise and model errors can be investigated. Previous studies evaluated the performance of the SDIM using only simulated FRF measurements obtained from a two-dimensional structural model. In addition, the disparity between the two-dimensional model used by the SDIM used to identify damage and the measurements obtained from the three-dimensional test structure is analyzed. The research results indicate that the SDIM is able to accurately detect structural damage to individually damaged members or to within a damaged floor, with few false damages identified. The SDIM provides an easy to use, visual, and accurate algorithm and its performance compares favorably to performance of the various damage detection algorithms that have been proposed by researchers to detect damage in the three-dimensional structural benchmark problem.

Doctor of Philosophy / Department of Civil Engineering / Asadollah Esmaeily / Civil structures are susceptible to damages over their service lives due to aging, environmental loading, fatigue and excessive response. Such deterioration significantly affects the performance and safety of structure. Therefore, it is necessary to monitor the structural performance, detect and assess damages at the earliest possible stage in order to reduce the life-cycle cost of structure and improve its reliability. Over the last two decades, extensive research has been conducted on structural health monitoring and damage detection. In this study, a signal-based pattern-recognition method was applied to detect structural damages with a single or limited number of input/output signals. This method is based on the extraction of sensitive features of the structural response under a known excitation that present a unique pattern for any particular damage scenario. Frequency-based features and time-frequency-based features of the acceleration response were extracted from the measured vibration signals by Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT) to form one-dimensional or two-dimensional patterns, respectively. Three pattern recognition algorithms were investigated when performing pattern-matching: (1) correlation, (2) least square distance, and (3) Cosh spectral distance. To demonstrate the validity and accuracy of the method, numerical and experimental studies were conducted on a simple small-scale three-story steel building. In addition, the efficiency of the features extracted by Wavelet Packet Transform (WPT) was examined in the experimental study. The results show that the features of the signal for different damage scenarios can be uniquely identified by these transformations. Suitable correlation algorithm can then be used to identify the most probable damage scenario. The proposed method is suitable for structural health monitoring, especially for the online monitoring applications. Meanwhile, the choice of wavelet function affects the resolution of the detection process and is discussed in the “experimental study part” of this report.

A method that can be used to detect damage in structures is developed. This method is based on the convexity of the geometric interpretation of the eigenvalue problem for undamped positive definite systems. The damage detection scheme establishes various damage scenarios which are used as failure sets. These scenarios are then compared to the structure's actual response by measuring the natural frequencies of the structure and using a Euclideian norm. Mathematical models were developed for application of the method on a cantilever beam. Damage occurring at a single location or in multiple locations was estalished and studied. Experimental verification was performed on serval prismatic beams in which the method provided adequate results. The exact location and extent of damage for several cases was predicted. When the method failed the prediction was very close to the actual condition in the structure. This method is easy to use and does not require a rigorous amount of instrumentation for obtaining the experimental data required in the detection scheme. / Ph. D.

No description available.

A time-domain model-based crack diagnostic methodology using vibration data is presented. Most of the damage detection methods proposed to date are based on modal parameters and are limited by the loss of information caused by data reduction and by the implicit assumption of linearity. The use of time domain information permits the direct inclusion of the nonlinear behavior due to crack opening-closure cycles. In addition, very little information is lost, since no signal processing or parameter identification steps are involved. The proposed method is based on a continuous model for the transverse vibrations of beams consisting of partial differential equations of motion with varying coefficients to account for the presence of damage. In order to provide accurate representation of the structure's behavior over a broader frequency range, a new continuous cracked beam model including shear effects and rotatory inertia is developed using the Hu-Washizu-Barr variational method. The resulting equations of motion are discretized by a Galerkin method using local B-splines as test functions. The crack is assumed to be either fully open or fully closed, resulting in a bilinear system. The simultaneous identification of crack location and depth is performed by minimizing the norm of the differences between the numerical and experimental time responses to multiple excitations. Impact, low frequency sinusoidal and Schroeder--phased multisine inputs are investigated as potential excitation methods. The cost function to be minimized presents several local minima that are shown to be related to the length of the response records. A genetic algorithm is used to overcome the multimodal nature of the objective function. The methodology is validated through simulated identifications of several damage scenarios. The importance of the inclusion of the nonlinear behavior is addressed, and the effects of model uncertainties and measurement noise are quantified in terms of minimum identifiable crack size. / Ph. D.

Many studies have attempted to detect structural damage by examining differences in the frequency response functions of a structure before and after damage. In an experimental setting, this variation can not be attributed solely to the addition of damage. Other sources of variation include testing and structure variation. Examples of testing variation include the error introduced by modal parameter extraction, measurement noise, and the mass loading of the accelerometer. Structure variability is due to slight differences in the supposedly identical structures. Dimensional tolerancing is one example. This study began with six "identical" undamaged aluminum cylinders, of which three were later damaged to varying extents. The frequency response functions of the undamaged and damaged cylinders were measured. Also, the frequency response function of the same undamaged cylinder was measured multiple times to investigate testing variation. The contributions of testing, cylinder, and damage variation to the differences between cylinder responses was elucidated by specifically examining their frequency response functions in two ways: comparing the natural frequencies and directly investigating the entire frequency response function. The curvature of the frequency response functions was then used to determined the presence, location, and severity of the imparted damage. / Master of Science

We discuss a systematic methodology that leads to the reconstruction of the material profile of either single, or assemblies of one-dimensional flexural components endowed with Timoshenko-theory assumptions. The probed structures are subjected to user-specified transient excitations: we use the complete waveforms, recorded directly in the time-domain at only a few measurement stations, to drive the profile reconstruction using a partial-differential-equation-constrained optimization approach. We discuss the solution of the ensuing state, adjoint, and control problems, and the alleviation of profile multiplicity by means of either Tikhonov or Total Variation regularization. We report on numerical experiments using synthetic data that show satisfactory reconstruction of a variety of profiles, including smoothly and sharply varying profiles, as well as profiles exhibiting localized discontinuities. The method is well suited for imaging structures for condition assessment purposes, and can handle either diffusive or localized damage without need for a reference undamaged state. / text