Force Identification Based on Response Signals Captured with High-Speed Three-Dimensional Digital Image Correlation.

Structural Health Monitoring (SHM) systems allow three types of diagnostic tasks to be performed, namely damage identification, loads monitoring, and damage prognosis. Only if all three tasks are correctly fulfilled can the useful remaining life of a structure be estimated credibly. This paper deals with the second task and aimed to extend state-of-the-art in load identification, by demonstrating that it is feasible to achieve it through the analysis of response signals captured with high-speed three-dimensional Digital Image Correlation (HS 3D-DIC). The efficacy of the proposed procedure is demonstrated experimentally on a frame structure under broadband vibration excitation. Full-field vibration displacement signals are captured with the use of two high-speed cameras and processed with 3D-DIC. Loads are identified with two different algorithms based on inverting the Frequency Response Function (FRF) matrix and modal filtration (MF). The paper discusses both methods providing their theoretical background and experimental performance.

Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks.

Guided waves are a potent tool in structural health monitoring, with promising machine learning algorithm applications due to the complexity of their signals. However, these algorithms usually require copious amounts of data to be trained. Collecting the correct amount and distribution of data is costly and time-consuming, and sometimes even borderline impossible due to the necessity of introducing damage to vital machinery to collect signals for various damaged scenarios. This data scarcity problem is not unique to guided waves or structural health monitoring, and has been partly addressed in the field of computer vision using generative adversarial neural networks. These networks generate synthetic data samples based on the distribution of the data they were trained on. Though there are multiple researched methods for simulating guided wave signals, the problem is not yet solved. This work presents a generative adversarial network architecture for guided waves generation and showcases its capabilities when working with a series of pitch-catch experiments from the OpenGuidedWaves database. The network correctly generates random signals and can accurately reconstruct signals it has not seen during training. The potential of synthetic data to be used for training other algorithms was confirmed in a simple damage detection scenario, with the classifiers trained exclusively on synthetic data and evaluated on real signals. As a side effect of the signal reconstruction process, the network can also compress the signals by 98.44% while retaining the damage index information they carry.

Indirect Measurement of Loading Forces with High-Speed Camera.

In the last few decades, there has been a significant increase in interest in developing, constructing, and using structural health monitoring (SHM) systems. The classic monitoring system should, by definition, have, in addition to the diagnostic module, a module responsible for monitoring loads. These loads can be measured with piezoelectric force sensors or indirectly with strain gauges such as resistance strain gauges or FBG sensors. However, this is not always feasible due to how the force is applied or because sensors cannot be mounted. Therefore, methods for identifying excitation forces based on response measurements are often used. This approach is usually cheaper and easier to implement from the measurement side. However, in this approach, it is necessary to use a network of response sensors, whose installation and wiring can cause technological difficulties and modify the results for slender constructions. Moreover, many load identification methods require the use of multiple sensors to identify a single force history. Increasing the number of sensors recording responses improves the numerical conditioning of the method. The proposed article presents the use of contactless measurements carried out with the help of a high-speed camera to identify the forces exiting the object.

The Study of Localized Crack-Induced Effects of Nonlinear Vibro-Acoustic Modulation.

The nonlinear interaction of longitudinal vibration and ultrasound in beams with cracks is investigated. The central focus is on the localization effect of this interaction, i.e., the locally enhanced nonlinear vibro-acoustic modulation. Both numerical and experimental investigations are undertaken. The finite element (FE) method is used to investigate different crack models, including the bi-linear crack, open crack, and breathing crack. A parametric study is performed considering different crack depths, locations, and boundary conditions in a two-dimensional beam model. The study shows that observed nonlinearities (i.e., nonlinear crack-wave modulations) are particularly strong in the vicinity of the crack, allowing not only for crack localization but also for the separation of the crack-induced nonlinearity from other sources of nonlinearity.

Wavelet-Based Transmissibility for Structural Damage Detection.

Short-time, abrupt events-such as earthquakes and other shock loadings-often lead to damage that is difficult to detect in structures using output-only vibration measurements. The time-variant transmissibility is proposed to tackle this problem. The approach is based on two-dimensional wavelet power spectra. The time-frequency transmissibility and relevant coherence function are used for structural damage detection in structural elements in buildings. Numerical simulations and experimental tests are used in these investigations. The results are compared with the classical transmissibility and time-variant input-output wavelet approach. The paper shows that output-only measurements and wavelet-based transmissibility can be used to monitor abrupt damage-related changes to structural dynamics.