Basics of Data-Driven FDD Methods

Compared with signal analysis-based and model-based methods, data-driven FDD schemes can be implemented directly by sufficient use of information hidden in the abundant recorded data. Nowadays, a variety of advanced sensors can ensure implementation and promote development of the data-driven FDD methods. To our best knowledge, multivariate statistical analysis (MSA) and subspace identification method (SIM) are two parallel methods providing basic tools and techniques to deal with FDD problems in both stationary and dynamic operating conditions. Therefore, this chapter firstly describes the basics including MSA, SIM, together with the used test statistic, which serves as the fundamentals of this work; based on these basics, challenging topics of FDD applications to high-speed trains is then summarized.