Han Zhou – författare

This book investigates in detail some new spoof surface plasmon polaritons (SSPPs) structures and their applications to antenna. It introduces the working principle and radiation characteristics of directional antenna, omnidirectional antenna, reconfigurable antenna and phase-mode antenna based on SSPPs structure. Especially, the irregular SSPPs structure, such as T-shaped and m-shaped SSPPs structures, is introduced to low-profile end-fire antenna with vertical polarization; the rotated SSPPs structure is applied to CP end-fire antenna and omnidirectional antenna; PIN circuit combining with SSPPs structure is used to pattern reconfigurable antenna; the novel phase-mode SSPPs antennas with multi-modes are performed too.

This book proposes a continuous method to develop the potentialities of the SSPPs antenna. And the readers can study the method or ideas of the SSPPs antenna, even graft the methods to other SSPPs antenna.

The book is intended for undergraduate and graduate students who are interested in SSPPs antenna technology, researchers investigating high-performance antenna, and antenna design engineers working on multi-function antenna applications.

This book summarizes techniques of fault prediction, detection, and identification, all included specifically in the data-driven fault diagnosis requirements within industrial processes, drawing from the combination of data science, machine learning, and domain-specific expertise. In the modern industrial processes, where efficiency, productivity, and safety stand as paramount pillars, the pursuit of fault diagnosis has become more crucial than ever. The widespread use of computer systems, along with new sensor hardware, generates significant quantities of real-time process data. It has been frequently asked what could be done with both the real-time and archived historical data, to not only promising efficiency but providing prospect of a brighter, more resilient future. This book starts with the definition, related work, and open test-bed for industrial process fault diagnosis. Then, it presents several data-driven methods on fault prediction, fault detection, and fault diagnosis, with consideration of properties of industrial processes, such as varying operation modes, non-Gaussian, nonlinearity. It distills cutting-edge methodologies and insights which may inspire for industrial practitioners, researchers, and academicians alike.