E. Parloo

Force identification by means of in-operation modal models

In-operation modal analysis has become a valid alternative for structures where a classic forced-vibration test would be difficult if not impossible to conduct. The modelling of output-only data obtained from naturally excited structures is particularly interesting because the test structure remains in its normal in-operation condition during the test. One of the drawbacks of in-operation analysis is that part of the modal parameters can no longer be estimated. Consequently, the applicability of in-operation modal models remains somewhat restricted. For some in-operation applications, interest lies in the identification of forces that gave rise to measured response signals. In order to solve this ill-conditioned problem, a complete modal model of the structure is required. Recently, a sensitivity-based method was proposed for the normalization of operational mode shape estimates on a basis of in-operation modal models only. This method allows the reconstruction of complete modal models from output-only data. In this contribution, the possibility of using such re-completed in-operation modal models for the identification of localized forces is explored.

Identification of modal parameters including unmeasured forces and transient effects

In this paper, a frequency-domain method to estimate modal parameters from short data records with known input (measured) forces and unknown input forces is presented. The method can be used for an experimental modal analysis, an operational modal analysis (output-only data) and the combination of both. A traditional experimental and operational modal analysis in the frequency domain starts respectively, from frequency response functions and spectral density functions. To estimate these functions accurately sufficient data have to be available. The technique developed in this paper estimates the modal parameters directly from the Fourier spectra of the outputs and the known input. Instead of using Hanning windows on these short data records the transient effects are estimated simultaneously with the modal parameters. The method is illustrated, tested and validated by Monte Carlo simulations and experiments. The presented method to process short data sequences leads to unbiased estimates with a small variance in comparison to the more traditional approaches.

Maximum likelihood identification of non-stationary operational data

Abstract In-operation modal analysis has become a valid alternative for structures where a classic input–output test would be difficult if not impossible to conduct. Due to practical considerations, measurements are sometimes performed in patches (roving sensor setups) instead of covering the entire structure at once. In practice, one is often confronted with non-stationary ambient excitation sources (e.g., wind, traffic, waves, etc.). Since the scaling of operational mode shape estimates depends on the unknown level of the ambient excitation, an extra effort is required in order to correctly merge the different parts of the mode shapes. In this contribution, two different approaches, for merging operational mode shapes from non-stationary data, are proposed. Both methods are based upon a single maximum likelihood estimation procedure. For comparison and validation, both techniques were applied to non-stationary data sets obtained by scanning laser vibrometry as well as the Z24 bridge bench mark data.

Modal parameter estimation and monitoring for on-line flight flutter analysis

The clearance of the flight envelope of a new airplane by means of flight flutter testing is time consuming and expensive. Most common approach is to track the modal damping ratios during a number of flight conditions, and hence the accuracy of the damping estimates plays a crucial role. However, aircraft manufacturers desire to decrease the flight flutter testing time for practical, safety and economical reasons by evolving from discrete flight test points to a more continuous flight test pattern. Therefore, this paper presents an approach that provides modal parameter estimation and monitoring for an aircraft with a slowly time-varying structural behaviour that will be observed during a faster and more continuous exploration of the flight envelope. The proposed identification approach estimates the modal parameters directly from input/output Fourier data. This avoids the need for an averaging-based pre-processing of the data, which becomes inapplicable in the case that only short data records are measured. Instead of using a Hanning window to reduce effects of leakage, these transient effects are modelled simultaneously with the dynamical behaviour of the airplane. The method is validated for the monitoring of the system poles during flight flutter testing.

Increased reliability of reference-based damage identification techniques by using output-only data

Abstract During the past few years, a considerable number of damage identification techniques have been proposed and successfully tested on vibration data obtained from mechanical structures. Most vibration-based methods identify damage by interpreting measured changes in modal parameters. In practice, damage identification problems can occur due to minor changes in the boundary conditions of the test set-up especially if classic input–output vibration measurements are required for the diagnosis of a lightweight structure. In this contribution, a comparison is made between an input–output and output-only damage identification set-up for an aluminum beam structure suffering from fatigue-induced crack formation.

User-assisting tools for a fast frequency-domain modal parameter estimation method

Abstract Recently, the least-squares complex frequency-domain (LSCF) estimator has been developed for modal analysis applications. This contribution elaborates in more detail the fast derivation of stabilisation charts and uncertainty bounds for the estimated poles. An alternative representation for the stabilisation chart as well as a robust cluster algorithm to identify clusters of poles using the chart information is presented. Based on the clusters, uncertainty bounds for the poles and an automation of the pole selection process are derived. The relation of these “variances” with the stochastic variances (or confidence bounds) introduced by the noise on the measurements is compared by means of Monte-Carlo simulations. The use of alternative representation for the stabilisation chart in combination with the robust cluster analysis as well as the availability of uncertainty bounds for the modal parameters, assist the user with the performance of an accurate modal parameter estimation.

Combined damage detection techniques

Abstract Linear damage detection techniques are used frequently because of their simplicity and their easy interpretation. In this paper, it will be shown however that linear techniques are not very robust with respect to environmental changes and interstructure variability. With the aid of experimental results it will be demonstrated that non-linear damage detection techniques, although being more complex, are less sensitive to these effects. In addition, two damage detection approaches will be proposed that combine the advantages of different classes of techniques. Firstly, a combined linear–non-linear approach is described. In the second proposed method, static and dynamic measurement techniques will be combined. Using experimental damage detection results, it will be shown that both proposed combined techniques are less sensitive to environmental changes while leading to easy interpretation of results.

AN ON-LINE COMBINED LINEAR-NONLINEAR FATIGUE CRACK DETECTION TECHNIQUE

Abstract To monitor the structural health during fatigue tests, classical nondestructive tests (ultrasonic inspection, liquid penetration, eddy current, etc.) are usually performed at regular time instances. Unfortunately, the fatigue tests should be interrupted to use these techniques. In addition, a large amount of user interaction is required. In this article, vibration features are used to detect cracks on-line with the execution of a fatigue test. To perform this task, an experimental strategy is developed to simultaneously estimate static and dynamic as well as linear and nonlinear vibration features. By means of these features the sensitivity of static versus dynamic and linear versus nonlinear damage detection techniques will be qualified. Finally, it will be shown that by using nonlinear identification techniques, additional information on the damage scenario can be extracted. The validation will be done on a steel beam with a propagating fatigue crack.

Linear and nonlinear damage detection using a scanning laser vibrometer

Because a Scanning Laser Vibrometer (SLV) can perform vibration measurements with a high spatial resolution, it is an ideal instrument to accurately locate damage in a structure. Unfortunately, the use of linear damage detection features, as for instance FRFs or modal parameters, does not always lead to a successful identification of the damage location. Measurement noise and nonlinear distortions can make the damage detection procedure difficult. In this article, a combined linear-nonlinear strategy to detect and locate damage in a structure with the aid of a SLV, will be proposed. To minimize the effect of noise, the modal parameters will be estimated using a Maximum Likelihood Estimator (MLE). Both noise and nonlinear distortion levels are extracted using the residuals of a two-dimensional spline fit. The validation of the technique will be performed on SLV measurements of a delaminated composite plate.

IDENTIFICATION OF CONTINUOUS-TIME NOISE MODELS

Abstract Current methods identify the physical parameters of continuous-time ARMA(X) processes via discrete-time approximations. Based on a frequency domain maximum likelihood estimator described in Ljung (1999), this paper proposes an exact continuous-time noise modeling approach. The theory is illustrated on real measurement examples.