Online Self-Calibrating Precision Scanning Fiber Technology with Piezoelectric Self-Sensing

Abstract

The scanning fiber technology was invented at the University of Washington more than a decade ago as a novel imaging modality within an extremely compact form factor. Since then, the mechanical design has improved from early 500Hz specimens to recent 11.5kHz prototypes, and systems have been built for pilot studies in minimally invasive surgery and fluorescence imaging with probe diameter as small as 1.2mm. However, the control system (which is crucial for high quality imaging) for these scanning fiber prototypes have not advanced beyond open-loop implementations due to the lack of an appropriate miniature sensor. The absence of closed-loop or adaptive control hinders the performance of scanning fiber systems in practical operating environments. This dissertation presents three major advancements to the scanning fiber technology. Firstly, this work introduces novel piezoelectric self-sensing methods to the scanning fiber architecture. Not only does piezoelectric self-sensing provide an online miniature sensor, it also functions without any modification to the mechanical structure by using the same piezoelectric elements for both actuation and sensing. A new piezoelectric self-sensing circuit is also described and shown to provide online measurements of scan tip deflection that was hitherto unavailable. Secondly, this work introduces new electromechanical modeling approaches together with methods for empirical system identification using piezoelectric self-sensing. The nature of piezoelectricity and integration of the new self-sensing circuit mean that the scanning fiber system should be modeled in both the mechanical and electrical domains. This work presents both a physically interpretative and a modal-analysis-driven electromechanical model verified with the actual scanning fiber system. System identification and model reduction techniques are also developed that extract empirical models then used for accurate scan control. Finally, this dissertation presents the development and verification of two new adaptive control schemes using piezoelectric self-sensing. An adaptive feedforward approach and a run- to-run optimization controller are introduced and experimentally demonstrated to outperform de- facto open-loop control methods even under time-varying mechanical and thermal stress. Together, these contributions enable for the first time self-calibration by the scanning fiber device to maintain high image quality through changing operating conditions, greatly improving the usability and maturity of the scanning fiber technology.