Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT

Abstract

A proper system identification method is of great importance in the process of acquiring an analytical model that adequately represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach for system diagnostics, the frequency domain identification techniques have primarily been considered for offline commissioning purposes. This paper addresses issues in the online frequency domain identification of a flexible two-mass mechanical system with varying dynamics, and a particular attention is paid to detect the changes in the system dynamics. An online identification method is presented that is based on a recursive Kalman filter configured to perform like a discrete Fourier transform (DFT) at a selected set of frequencies. The experimental online identification results are compared with the corresponding values obtained from the offline-identified frequency responses. The results show an acceptable agreement and demonstrate the feasibility of the proposed identification method.

Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

“…The proposed online identification routine is validated with the experimental two-mass-system used in (Nevaranta et al, 2015b) and depicted in Figure 6. The rollers are driven by frequency-converter-supplied permanent magnet synchronous motors (PMSM), and a programmable logic controller (PLC) is used for data acquisition and to implement the excitation signals, PI controller, and references.…”

“…As discussed in (Jenssen and Zarrop, 1994) and (Nevaranta et al, 2015b), in the case of a multi-sine excitation signal the state-space realization Eq. (12)and Eq.…”

“…(24), where K is the spring constant, and D is the damping constant of the belt material. A more detailed discussion on the mechanical system considered in this paper can be found in (Nevaranta et al, 2015b).…”

“…Motivated by the features of the Kalman-filter-based short-time DFT identification routines proposed in (Parker and Bitmead, 1987), (Nevaranta et al, 2015b) for frequency response identification of open-loop and closed-loop systems using a multi-sine excitation signal, the objective of this paper is to study the same routine in the case of a swept chirp excitation signal. In particular, the main idea of using the Kalman filter for estimating time-varying signals in a complex form is considered, but here the knowledge of the time-varying frequency of the excitation signal is used to update Kalman gains.…”