An overview of the current state of knowledge and technology on techniques and procedures for signal processing, analysis, and accurate inference for transportation noise and vibration
Rafał Burdzik, Diyar Khan
Abstract
This review paper provides a thorough review of the current state of knowledge and technology in noise and vibration research within the transport sector, with a particular focus on signal processing, analysis methods, and inference techniques. This paper highlights the practical relevance of these advancements by addressing the engineering challenges associated with diverse transport modes, including road, rail, air, and marine systems. This review paper examines the cutting-edge techniques such as time–frequency analysis, wavelet transforms , and machine learning algorithms , using a systematic approach based on the PRISMA framework. These methods not only improve the detection, characterization, and mitigation of noise and vibration but also enable accurate diagnostics and informed management strategies essential for the engineering domain. Key practical applications include the use of advanced digital signal processing techniques in vibration-based structural health monitoring and the use of machine learning for noise reduction and inference. Additionally, the historical evolution of noise and vibration research is explored, showcasing the interdisciplinary integration of artificial intelligence in contemporary engineering approaches. The study identifies critical research gaps, such as the need for adaptive algorithms and real-time processing capabilities, while emphasizing the emerging role of electric vehicles and artificial intelligence-driven technologies in creating quieter, more efficient transport systems. By addressing these challenges, this work contributes to safer, more sustainable transportation infrastructures, offering a valuable resource for researchers, engineers, and policymakers. The findings highlight the transformative potential of advanced signal processing in tackling real-world noise and vibration challenges, fostering engineering solutions that enhance transportation safety and sustainability .