In this paper, the use of the combined deterministic-stochastic subspace identification algorithm for the experimental modal analysis of mechanical structures is discussed. The algorithm requires artificial forces to be applied to the structure, so it can be used for experimental modal analysis (EMA). The algorithm can also be used for operational modal analysis (OMA), since the excitation level of the artificial force(s) can be low compared to the excitation level of the ambient forces. Both the modes that are artificially excited and those that are excited by the ambient forces are identified. This type of operational modal analysis is called an OMAX analysis (Operational Modal Analysis with eXogenous inputs) [1]. The main advantages of OMAX over OMA are that the modes that are excited by the artificial forces can be scaled to unity modal mass and that a higher number of modes can be identified.

Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis

Piezoelectric energy harvester for rolling bearings with capability of self-powered condition monitoring

Dynamically synergistic regulation mechanism for rotation energy harvesting

Enhanced swing electromagnetic energy harvesting from human motion

Multi-parameter theoretical analysis of wearable energy harvesting backpacks for performance enhancement

Bistable energy harvesting backpack: Design, modeling, and experiments

System parameters identification of nonlinear bistable structures has attracted considerable interest because the performance enhancement of energy harvesting and vibration control is significantly dependent on the model parameter of nonlinear systems. Therefore, a two-stage subspace method is proposed to identify the critical parameters in the system equation of nonlinear bistable piezoelectric structures. The dynamic equation of nonlinear bistable piezoelectric structures is separated into an underlying linear electromechanical coupling equation and a nonlinear mechanical equation. At first, for the underlying linear electromechanical coupling equation, a force–displacement subspace is constructed to identify the linear mass, damping and stiffness. Meanwhile, a velocity–voltage subspace is created for the identification of the electromechanical coupling coefficient. Next, for the nonlinear mechanical equation, the nonlinear restoring force in bistable structures can be estimated by the extended nonlinear frequency response function. Numerical simulation on a magnetic coupled bistable piezoelectric structure is performed to investigate the influence of frequency-swept responses, the noise intensity and polynomial order on identification accuracy. Experimental measurement of a magnetic coupled asymmetric bistable piezoelectric beam is conducted under different excitation conditions. Experimental results demonstrate the effectiveness of the proposed identification method.

Zehao Hou

Papers

Enhanced swing electromagnetic energy harvesting from human motion

Multi-parameter theoretical analysis of wearable energy harvesting backpacks for performance enhancement

Bistable energy harvesting backpack: Design, modeling, and experiments

Parameter identification of nonlinear bistable piezoelectric structures by two-stage subspace method

Nonlinear Restoring Force Identification of Strongly Nonlinear Structures by Displacement Measurement