# Sensors and Measurement Systems for Marine Engineering Applications
## 2 An Overview of the Published Articles  
In the first article, [PERSON] et al. (contribution 1) present a novel rotational-linear triboelectric nanogenerator (RL-TENG) that converts rotational motion to linear motion to harvest rotational energy. The device employs ZnO nanoparticles as a triboelectric material, demonstrating a modular design for various applications. The RL-TENG design offers several advantages, including reduced wear and increased temperature during operation, compared to traditional rotational tribogenerators. This technology has significant implications for maritime applications, particularly in wind energy harvesting for powering remote monitoring systems or other low-power devices. In the second article, [PERSON] et al. (contribution 2) introduce a mass air flow sensor designed for low- and medium-power internal combustion engines in the marine industry. The sensor fabrication process is based on additive manufacturing and PCB technology. The complex design of the sensing element housing geometry, which is manufactured through 3D printing, is based on standard airfoil geometry, while it is derived through suitable CFD simulations. The key features of the proposed device are its low cost, fast on-site manufacturing, robustness, and simplicity, suggesting numerous potential applications in marine engineering. In the third article, [PERSON] et al. (contribution 3) present a case study of super-long steel pipelines floating offshore, focusing on controlling deformation and avoiding resonance for safety. Their study employs wireless communication equipment and aerial photography technology to monitor strain and vibration during construction. This monitoring method prevents excessive deformation, resonance, and the destruction of anticorrosive coatings during floating transportation. The obtained results provide a detailed strain and modal analysis as well as effective monitoring technology for offshore steel pipeline transportation safety. In the fourth article (contribution 4), [PERSON] et al. elaborate on a novel MEMS piezoresistive pressure sensor designed to operate under harsh environmental conditions. The specific sensor demonstrates adequate linearity and sensitivity over a wide operating range, while a digital temperature compensation system impedes linearity drift due to temperature variation. The specific technology has significant implications for maritime applications, particularly in harsh environments, where robust and accurate pressure sensing is required. In the fifth article, [PERSON] et al. (contribution 5) propose a novel Principal Component Analysis integrating a Long Short-Term Memory Network (PCA-LSTM) model for predicting the productivity of cutter suction dredgers. The developed model involves operational parameters that are based on mechanism analysis, while it is considered a deep learning-based approach capable of dealing with operation series data with a special memory mechanism. The specific methodology has the potential to improve the efficiency and productivity of dredging operations, leading to cost savings and reduced environmental impacts. In the sixth article, [PERSON] et al. (contribution 6) present a novel method for measuring ocean surface currents in the Kuroshio region using Gaofen-3 SAR data. The developed method, which combines sub-aperture processing and least-squares (LS) technology to measure current vectors, demonstrates the capability of the Gaofen-3 SAR to accurately retrieve the ocean surface current field in the Kuroshio region. The specific methodology has significant implications for climate studies and maritime navigation in dynamic oceanic environments. In the seventh article, [PERSON] et al. (contribution 7) present a method for identifying engine malfunctioning through instantaneous crankshaft torque (ICT) measurement analysis. Briefly, this study demonstrates the usefulness of engine ICT as a nonintrusive diagnostic measurement, allowing for quick and less resource-intensive identification of engine malfunctions.