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A new noniterative frequency domain parameter estimation technique is proposed. It is based on a weighted total least squares approach, starting from multiple input multiple output frequency response functions. One of the specific advantages of the technique lies in the very stable identification of the system poles as a function of the specified system order, leading to easy-to-interpret stabilization diagrams. This implies a potential for automating the method and to apply it to “difficult” estimation cases. Several real-life case studies are discussed, one related to holographic modal analysis in the medium frequency range, one to the modal testing of a fully trimmed vehicle.

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Abstract. Comfort, road holding and safety of passenger cars are mainly influenced by an appropriate design of suspension systems. Improvements of the dynamic behaviour can be achieved by implementing semi-active or active suspension systems. In these cases, the correct design of a well-performing suspension control strategy is of fundamental importance to obtain satisfying results. Operational Modal Analysis allows the experimental structural identification in those that are the real operating conditions: Moving from output-only data, leading to modal models linearised around the more interesting working points and, in the case of controlled systems, providing the needed information for the optimal design and verification of the controller performance. All these characters are needed for the experimental assessment of vehicle suspension systems. In the paper two suspension architectures are considered equipping the same car type. The former is a semi-active commercial system, the latter a novel prototypic active system. For the assessment of suspension performance, two different kinds of tests have been considered, proving ground tests on different road profiles and laboratory four poster rig tests. By OMA-processing the signals acquired in the different testing conditions and by comparing the results, it is shown how this tool can be effectively utilised to verify the operation and the performance of those systems, by only carrying out a simple, cost-effective road test.

The output-only vibration-based structural health monitoring problem is addressed as the task of detecting damages modeled as changes in the eigenstructure of a linear dynamic system. The proposed damage detection algorithm is based on a residual generated from a subspace-based covariance-driven identification method and on the statistical local approach to the design of detection algorithms. This algorithm computes a global test, which performs a sensitivity analysis of the residuals to the damages, relative to uncertainties and noises. Numerical results are reported, which show the efficiency of the proposed method. They have been obtained on a geometrically simple test article designed, assembled and tested dynamically under impact and random shaker excitation. The method allows detecting damage in an early stage, and it does not require the extraction of the modal parameters from each newly collected data set. This characteristic is very well suited for monitoring purposes: it does not need continuous user interaction and it can easily be made automatic.