Papers by Author: Claus Peter Fritzen

Abstract: The Structural Health Monitoring process includes several steps like feature extraction and probabilistic decision making, which need some form of data fusion and information condensation. These take place after data acquisition and before being able to decide, if a monitored structure has faced damage. Although feature selection is an important step, the processing and suitable preparation of these data are significant, influencing the potential of decision making in various ways. With Self-Organizing Maps (SOM) a multi-purpose instrument for these tasks of pattern recognition and data interpretation is presented here. Self-Organizing Maps belong to the group of artificial neural networks and by using the special map character provide the opportunity of additional visualization. Especially when monitoring a structure over a long period of time, environmental changes often occur, which can mask the effects of damage on the dynamic behavior of the structures. As one potential application of SOM, the possibility of distinguishing between environmental changes and damage of the structure is shown. In this application a self-organizing network is trained with data of the undamaged structure and via calculation of the distance to the map a damage indicator is developed. Moreover, the distinction between different damage modes of piezoelectric sensors is presented using SOM as a tool of pattern recognition and visualization. This application uses data recorded from different damage modes extracted from one specimen of a piezoelectric element. The trained network can be compared with other piezoelectric elements mounted in a similar way to be able to detect possible sensor damage. This helps avoiding false alarms even under changing environmental conditions. Both applications have been successfully used to analyze experimental data on coupon level showing the applicability of the presented concepts.

Abstract: Acoustic Emission (AE) techniques are used for the structural health monitoring (SHM) of civil, aeronautic and aerospace structures. In order to depart from the traditional reliance on parameter based analysis, AE diagnostic techniques require the analysis of wave propagation phenomena and the use of predictive modelling tools to improve the monitoring capabilities and provide reliable health monitoring. Additionally, modal based techniques offer potential for optimization of sensor networks in terms of sensor placement and number of sensors, increased source location accuracy and to get an insight into the source mechanisms. If the modes of propagation can be recognised in the received AE signals, then it would be possible to discriminate between damage types. On that account, the present paper develops two methodologies that are useful tools for the investigation and design of wave propagation based SHM systems established upon modal analysis. Firstly, a higher order plate theory for modelling disperse solutions in elastic and viscoelastic fibre-reinforced composites is proposed in order to investigate the radiation and attenuation of Lamb waves in anisotropic media. Second, spectral flat shell elements are used for the simulation of guided waves in shell structures. Numerical simulations and experiments validate the models and demonstrate that material anisotropy has a strong influence on the velocities, attenuation and acoustic energy for the different modes of propagation. It is expected that the presented methodologies may contribute to offer a higher computational efficiency and simplicity in comparison to traditional methods, and enable the design shortening time and cost of development of Lamb wave based damage detection systems for a rapid transfer from laboratory to in-service structures.

Abstract: During high-cycle-fatigue loading of metastable austenitic steel AISI304L, the elastic anisotropy between neighboring grains causes the occurrence of stress peaks at grain boundaries, which again act as crack nucleation sites. This is in particular the case at twin boundaries. Cyclic crack tip plasticity leads to a transformation from  austenite to ´ martensite when different slip bands are activated, alternating during their operation. By means of in-situ fatigue testing in a scanning electron microscope (SEM) in combination with electron back-scattered diffraction (EBSD), the distributions of grain size, geometry, and crystallographic orientation relationship were correlated with the local occurrence of slip, martensite formation and fatigue-crack initiation and propagation. It was shown that the extent of martensite formation ahead of a propagating crack increases with increasing crack length and eventually, due to its higher specific volume, gives rise to transformation-induced crack-closure effects. The variation in the crack-propagation rate depending on the local microstructure was simulated by means of a short crack model, where the displacement fields within the crack, the adjacent plastic zone and the grain boundaries in combination with the martensite volume increase strain are superimposed by means of a boundary-element approach.

Abstract: In recent years many SHM approaches based on elastic waves that are generated and sensed by surface-bonded piezoelectric patches have been developed. Some of those utilize wave propagation phenomena; others use changes in the electromechanical impedance to detect structural damage. The capability of most approaches strongly depends on adequate choice of SHM system parameters like excitation signals and actuator/sensor types and positions. For this reason there is a growing interest in efficient and accurate simulation tools to shorten time and cost of the necessary tedious pretests. To detect small damage generally high frequency excitation signals have to be used. Because of this a very dense finite element mesh is required for an accurate simulation. As a consequence a conventional finite element simulation becomes computationally inefficient. A new approach that seems to be more promising is the time domain spectral element method. This contribution presents the theoretical background and some results of numerical calculations of the propagation of waves. The simulation is performed using the spectral element method (SEM), which leads to a diagonal mass matrix. Besides a significant saving of memory this leads to a crucial reduction of complexity of the time integration algorithm for the wave propagation calculation. A new approach to simulate the E/M impedance using time domain spectral elements is shown. An example demonstrates a good correlation of simulation and measurement data, so that the proposed simulation methodology seems to be a promising tool to make impedance based SHM systems more efficient, especially regarding the necessary parameter studies.

Abstract: A novel sensor placement criterion is proposed for structural health monitoring after five influencing criteria are critically reviewed. The objective of the proposed criterion is to achieve best identification of modal frequencies and mode shapes through almost unbiased estimation of modal coordinates. The proposed criterion derived by the Representative Least Squares method depends on both the characteristics and the actual loading situations of a structure. It selects sensor positions with the best subspace approximation of the vibration responses from the linear space spanned by the mode shapes. Furthermore, the connection between the Effective Independence and the approximate Representative Least Squares estimator is obtained through matrix perturbation analysis. It is found that the Effective Independence is a step-by-step approximation to that of the Representative Least Squares criterion.

Abstract: During this decade, piezoelectric elements are explored and applied successfully in SHM, which has positioned them as an enabling technology for damage assessment. When permanently bonded to the structure, they provide the bi-directional energy conversion, which is used in impedance-based SHM. In this method, the variations of the structure’s impedance are monitored by piezoelectric elements. However, before experiments are performed, it is important to position correctly the piezoelectric elements on the structure. Therefore, the capability of piezoelectric actuators is explored under the aspect of sensor position. This work presents the investigation of sensing ability of surface-bonded piezoelectric element using numerical simulation and experiment. The results of numerical and experimental investigation are shown in this paper, which illuminates the model in the aluminium plate could be used to predict the state of it. In the experimental investigation, it also shows the factors which influence strongly the capability of sensor detection. Dealing with high frequency excitation, calculation requires a very dense finite element mesh, hence, the spectral element method (SEM) is chosen as model-based method, which is much more efficient than classical FEM. The structure, self-sensing elements as well as damage are modelled, from which the spectra of E/M impedance is computed. It gives the theoretical basis for the experiment design. The numerical results are verified and validated by experimental investigation. With such a numerical tool, the efficiency of the E/M impedance method can be clearly improved with respect to the determination of suitable piezoelectric element locations.

Abstract: In the present paper examples for propagating and non-propagating conditions of slip bands and short fatigue cracks in a ferritic-austenitic duplex steel are given, which were quantified by means of SEM in combination with automated EBSD. To classify the results within the scope of predicting the service life under HCF- and VHCF-loading conditions a numerical model based on the boundary-element method has been developed, where crack propagation is described by means of partially irreversible dislocation glide on crystallographic slip planes in a polycrystalline model microstructure (Voronoi cells). This concept is capable to account for the strong scattering in fatigue life for very small strain amplitudes and to contribute to the concept of tailored microstructures for improved cyclic-loading behaviour.

Abstract: For purposes of monitoring and damage prognosis it is important to know the external loads which act on a structure. The knowledge of these loads enables us to make an assessment of damage after extreme events and updated forecasts of the remaining life-time. In many practical applications it is not possible to measure the forces e.g. resulting from wind loads or traffic directly. Therefore, these forces are determined indirectly from dynamic measurements. In this contribution, an updated overview of available time domain load reconstruction methods is presented. An attempt of highlighting the main advantages and disadvantages of different approaches, which are used in engineering is done. The importance of sensors type as well as their locations is considered for each approach. Finally, the methods applicability to real structures, where the online reconstruction plays an important role, is discussed.

Abstract: This paper presents a combined approach for sensor fault identification looking for changes within one channel on one hand and for changes between the different channels on the other hand. The first method is based on the identification of autoregressive (AR) models from the reference time signals for each sensor channel separately. The reference models are then used for the prediction of the future sensors signals. The statistical properties of the residuals between this prediction and the true measurement allow a statement about changes of the sensor signals. The second method is based on the concept of mutual information between two signals X and Y from two different sensors. Mutual information or transinformation measures the information about the channel X that is shared by Y. This requires a certain redundancy of information represented in the different sensor signals. It can be seen that the mutual information changes as soon as a sensor fault occurs because the sensor fault information is not present in the other sensor signals.

Abstract: The electro-mechanical (E/M) impedance-based method is one important and effective method in damage detection. The basic concept of the impedance method is to monitor the variations in the structural mechanical impedance spectrum caused by damage in the structure. Comparing the impedance spectrum to a baseline measurement of the undamaged structure, the real part of the E/M impedance reflects the state of structural health in the local area, therefore, the structural damage can be localized, a local-area self-sensing method is implemented. In this paper, an aluminium plate mounted on an electromagnetic shaker is used to detect growing fatigue damage using the impedance method. The growing damage is documented by an increase of the indicators. For the case of a static artificial damage the concept is also demonstrated to an Airbus A320 fuselage part using 9 self-sensing elements on the stringers.