7.2 Ingenieurbau
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- 7.2 Ingenieurbau (15) (entfernen)
In the last three decades, the vibrations of many floors and bridges have been measured. The contribution shows some evaluation methods, experimental results and some modelling and theoretical results. Simple evaluation methods have been developed for single and coupled floors. Two coupled beams have been measured in good agreement with the theory. A more complex coupling model has been found for a large wooden floor in a castle consisting of six floor bays which correlates well with the measurements. Damaged and intact poles have been tested by their natural frequencies and damping values, and a fair correlation between the degree of damage and the shift of the frequency. Road bridges have been analysed in detail and some examples are presented. Railway bridges and trains are studied for resonant excitation. The risk of resonance can be estimated in frequency domain by using axle-sequence spectra of the train and the natural frequencies of the bridge. A measurement example shows the amplification, but even stronger the cancellation of the subsequent axle responses. Several high-speed trains and freight trains have been analysed for their potential resonance amplification.
Fault detection for linear parameter varying systems under changes in the process noise covariance
(2020)
Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models – each estimated from data measured in a reference state – are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then conflicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
Changes in the measured response of structural systems can be an indication of structural damages. However, such changes can also be caused by the effect of varying environmental conditions. To detect, localize and quantify changes or damages in structural systems subject to varying environmental conditions, physics-based models of the structural systems have to be applied which explicitly account for the influence of ambient conditions on the structural behavior. Data obtained from the structural systems should be used to calibrate the models and update predictions. Bayesian system identification is an effective framework for this task. In this paper, we apply this framework to learn the parameters of two competing structural models of a reinforced concrete beam subject to varying temperatures based on static response data. The models describe the behavior of the beam in the uncracked and cracked condition. The data is collected in a series of load tests in a climate chamber. Bayesian model class selection is then applied to infer the most plausible condition of the beam conditional on the available data.
The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing.
This paper scopes the specialties of a hazard identification study for large and extra-large unmanned undersea vehicles (UUVs). A generic node/function structure is derived from different large and extra-large UUV designs, partially own vehicle designs from research projects, and partially from commercial vehicles. For each node, a short overview of its components and the proper function or operations is defined. A set of guide words is used to prompt a hazard discussion for each node, which identifies unwanted functions, resulting in potential hazards and unmitigated consequences. Related to the SafeMASS-Report from DNV, this work concentrates on selected topics of the bridge-related function on voyage, control & monitoring, and abnormal situations. For unmanned vehicles without any person on board, these three topics become more important for underwater vehicles with very limited connectivity or temporary disruptions of communication whereby an operator in a remote-control center could only be provided with rough vehicle or mission states. Therefore, vehicle control, whether in hard- or software, must handle most tasks belonging to the considered functions automatically or autonomously. Hence, the most appropriate reactions of the system to unwanted system
behavior must be implemented. This HAZID study could, on the one hand, be used as background for such an implementation, and on the other hand, it is used to verify the implemented actions on the risks and hazards.