# Vibration Isolation of a Surveillance System Equipped in a Drone with Mode Decoupling
## 1 Introduction
However, the weight of smart mobility plays a critical role in executing its mission, suggesting that passive optimization of a vibration isolator should be proceeded in advance before applying active control strategies for vibration isolation. In other words, passive vibration control should be completed before addressing the active control strategy to maximize the performance of a drone. For example, a drone could not fly for more than 20-25 min with the maximum payload; however, a drone with the light-weight smart inspection system flew for approximately 35 min, thereby executed its mission successfully [13]. Note that both active and passive strategies for vibration isolation are important to ensure the performance of a surveillance system. This study presents a method for vibration isolation of a surveillance system with mode decoupling, filling the gap in the previous studies. It also addresses system identification with the coupled multi-degree-of-freedom (DOF) model to accurately predict the effect of coupling on the degradation of a vibration isolation performance. Note that the method presented aims to optimize the location of natural frequency and decouple adjacent natural frequencies to vertical and horizontal directions without active control strategies to avoid adverse effects on the performance of the camera system transmitted from the rotors. A simple surveillance system with a rubber-type vibration isolator suffers from the coupled effects of natural frequencies in multi-DOF coordinates. It suggests that a vibration isolator should be implemented by reviewing the target system to mitigate issuesowing to the coupling effect. Furthermore, a decoupled dynamic model cannot predict this complex phenomenon, systematically limiting the vibration control of the system. On the contrary, the presented coupled multi-DOF model accurately predicts the coupling effects, showing that the location of the natural frequency in the vertical-horizontal direction is not sufficiently separated from the measured results. Therefore, it adversely affects surveillance performance. The optimal design was achieved through mode decoupling by changing the configuration of several vibration isolators based on system identification with a coupled multi-DOF model. Experiments have validated that the presented configuration can effectively isolate vibrations through mode decoupling. Specifically, the novelty and contribution of this study are as follows:  
* The entire process of vibration isolation with mode decoupling is presented as a countermeasure to minimize the vibration effects on the surveillance system. * System identification with a coupled multi-DOF model is presented to identify a problem of mode coupling on a vibration isolator and predict vibration isolation performance for optimized configuration of vibration isolators. * Design optimization of a vibration isolator is executed with the coupled multi-DOF model to separate vertical and horizontal natural frequencies by 1 Hz or more. * The effectiveness of the presented method is validated through experiments based on vibration isolation performance (VIP). The remainder of this paper is organized as follows. Section 2 presents the theories for system identification addressed in this study. This section includes the Equation of motion (EOM) for the decoupled and coupled systems, and Levenberg-Marquardt algorithm. Section 3 describes experimental vibration characterization including a theory for a frequency response function and procedures for modal testing. This section also includes a measurement scheme of vibration transmitted from rotors to a surveillance system. Section 4 presents results and suggestions. This section discusses initialization of a vibration problem on a mobile surveillance system and design optimization with the model-based system identification. The paper concludes with a summary and recommendations for future work in Section 5.