Time-Frequency Analysis.

Environmental and operational conditions effects on Lamb wave based structural health monitoring systems: A review

Recent progress in blue energy harvesting for powering distributed sensors in ocean

Structural health monitoring (SHM) is the continuous on-board monitoring of a structure's condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the state-of-the-art damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strain-based or conductivity-based methods and with additional sensors for environmental entities might yield a robust multi-sensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multi-sensor SHM approach is presented.

https://www.mdpi.com/1424-8220/20/3/826/pdf

Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures

Corrosion of 1020 carbon steel coupons in natural seawater over a 1-year period was more aggressive under strictly anaerobic stagnant conditions than under aerobic stagnant conditions as measured by weight loss and instantaneous corrosion rate (polarization resistance). Under oxygenated conditions, a two-tiered oxide layer of lepidocrocite/goethite formed. The inner layer was extremely tenacious and resistant to acid cleaning. Under anaerobic conditions, the corrosion product was initially a non-tenacious sulphur-rich corrosion product, mackinawite, with enmeshed bacteria. As more sulphide was produced the mackinawite was transformed to pyrrhotite. In both aerobic and anaerobic exposures, corrosion was more aggressive on horizontally oriented coupons compared to vertically oriented samples.

An Evaluation of Carbon Steel Corrosion under Stagnant Seawater Conditions

Ultrasonic guided wave (UGW) is one of the most commonly used technologies for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Because of its excellent long-range diagnostic capability, this method is effective in detecting cracks, material loss, and fatigue-based defects in isotropic and anisotropic structures. The shape and orientation of structural defects are critical parameters during the investigation of crack propagation, assessment of damage severity, and prediction of remaining useful life (RUL) of structures. These parameters become even more important in cases where the crack intensity is associated with the safety of men, environment, and material, such as ship’s hull, aero-structures, rail tracks and subsea pipelines. This paper reviews the research literature on UGWs and their application in defect diagnosis and health monitoring of metallic structures. It has been observed that no significant research work has been convened to identify the shape and orientation of defects in plate-like structures. We also propose an experimental research work assisted by numerical simulations to investigate the response of UGWs upon interaction with cracks in different shapes and orientations. A framework for an empirical model may be considered to determine these structural flaws.

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves.

An overview of maintenance management strategies for corroded steel structures in extreme marine environments

Corrosion-induced degradation in marine steel structures is highly dependent on the surrounding environmental conditions and sea water compositions that varies significantly around global sea water...

https://www.tandfonline.com/doi/pdf/10.1080/1478422X.2021.1904096

A dimensional metrology-based approach for corrosion measurement of ship grade steels exposed to various marine environmental conditions

It is quite straightforward to generate and acquire ultrasonic guided waves in metallic or composite structures to investigate structural defects; however, the interpretation and evaluation of the reflected/transmitted signal to extract useful information is a challenging task. This is primarily due to the dispersion and multimodal behavior of Lamb waves, which are dependent on the frequency of the excitation wave and the thickness of the material under investigation. These multimodal and dispersive behaviours lead to a complex waveform structure, and therefore require an advanced signal processing technique to decipher useful information in the time and/or frequency domains. For this purpose, due to its desirable mathematical properties, the Wigner–Ville distribution (WVD) is considered to be a powerful tool for generating time–frequency (TF) spectra and estimating the temporal and spectral features of this type of complex signal. However, due to its quadratic nature, undesirable cross-terms and spurious energies are also generated, which limit the readability and the interpretation of the spectrum. To suppress this effect, this paper describes the use of an autoregressive model based upon Burg’s maximum entropy method to modify the kernel of the discrete WVD. This technique was applied to ultrasonic Lamb wave signals obtained using various numerical and experimental configurations to extract the useful discriminatory spectral and temporal information required for the mode identification, localization, and quantification of structural damage. When used for damage localization, the proposed method precisely estimated the distance between two closely spaced notches in a metallic plate from different simulated noisy signals with a maximum uncertainty of 5%, based upon an excellent TF energy distribution. Moreover, the energy concentration (EC) of the TF energy distribution, in combination with the variation of its instantaneous frequency (IF) curve, was also effective in identifying the overlapping modes of the Lamb wave signal. Finally, for damage quantification, three TF-based damage indices, namely EC, TF flux, and IF, were extracted from five sets of specimens using the proposed TF scheme and used to train the regression model. Model testing proved that the damage indices have the potential to predict crack sizes precisely and reliably.

https://iopscience.iop.org/article/10.1088/1361-6501/abef3c/pdf

Muntazir Abbas

Papers

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves.

An overview of maintenance management strategies for corroded steel structures in extreme marine environments

A dimensional metrology-based approach for corrosion measurement of ship grade steels exposed to various marine environmental conditions

An advanced Wigner–Ville time–frequency analysis of Lamb wave signals based upon an autoregressive model for efficient damage inspection

Lamb wave damage severity estimation using ensemble-based machine learning method with separate model network