Efficient Full-Field Operational Modal Analysis Using Neuromorphic Event-Based Imaging

As an alternative to traditional sensing methods, video camera measurements offer a non-contact, cost-efficient, and full-field platform for operational modal analysis. However, video cameras record large amounts of redundant background data causing video processing to be computationally inefficient. This work explores the use of a silicon retina imager to perform operational modal analysis. The silicon retina provides an efficient alternative to standard frame-based video cameras. Modeling the biological retina, each silicon retina pixel independently and asynchronously records changes in intensity. By only recording intensity change events, all motion information is captured without recording redundant background information. This asynchronous event-based data representation allows motion to be captured on the microsecond scale, equivalent to traditional cameras operating at thousands of frames per second. With minimal data storage and processing requirements, the silicon retina shows promise for real-time vibration measurement and structural control applications. This study takes the first step toward these applications by adapting existing video frame-based modal analysis techniques to operate on event-based silicon retina measurements. Specifically, blind source separation and video motion processing techniques are used to automatically output vibration parameters from silicon retina data. The developed method is demonstrated on a cantilever beam.