Operational Modal Analysis (OMA) is the modal testing approach for the vast number of cases where it is impossible to measure the input forces that is acting on a structure during testing.
During the last decades OMA has been called many things. Some of the names are Output-Only Modal Analysis, Natural Input Modal Analysis, Ambient Vibration Testing, Ambient Response Testing and In-operation Modal Analysis. No matter what name is used, the algorithms and the way to test a structure are the same.
OMA was developed out from a need to know the modal parameters, i.e. natural frequencies, damping ratios and mode shapes, of structures that cannot be put into a test rig in a modal testing laboratory. This can either be because of the size of the structure or because of the desire to know the modal behaviour in-situ and using the natural source of excitation acting on the structure.
Historically, OMA has been widely used in onshore and offshore civil engineering but over the years its popularity has spread to many other engineering fields such as mechanical-, automotive-, aerospace-, and maritime engineering.
The required measurement setup is very simple as only response measurements are required. Any sensor capable of measuring the dynamic response of a structure can in principle be used. However, most popular sensors are still accelerometers.
For large civil engineering structures, the choice of accelerometers has for years been the Forced Balanced Accelerometer (FBA) capable of measuring both weak and strong motion due to their high dynamic range and low noise level. Lately, mems accelerometers have gained increased interest as well both because of price but also easier handling. Other widely used sensors for OMA are the velocity-based geophones, strain-gauges, laser vibrometers, Fiber Bragg Grating (FBG) and proximity probes.
The common basis for all OMA algorithms is the raw time series response measurements. Based on these measurements a wide range of OMA algorithms have been developed over the last many decades. The common assumption for all algorithms is that there are multiple independent and random input sources acting on the structure during testing. It is assumed that these broad-banded inputs are derived from so-called Gaussian white noise. If there are broad-banded input sources acting on the structure, there can also be other types of external forces like rotating equipment present.
ARTeMIS Modal is an open platform allowing response measurements to be uploaded through more than 20 different time series files formats. Response measurements can also be measured using the internal data acquisition module.
ARTeMIS Modal support single and multiple Test Setups testing. Either place all sensors at the structure and perform a single Test Setup or use rowing sensors keeping a few in fixed positions as references to produce multiple Test Setups.
ARTeMIS Modal includes up to three frequency domain operational modal analysis techniques derived from the user-friendly Frequency Domain Decomposition (FDD) technology. FDD utilizes the Singular Value Decomposition of the estimated spectral densities of the measured response. The FDD techniques available are:
All three techniques are based on peak-picking in the frequency domain using either automatic picking or manual picking using the mouse. Once picked, the mode shapes are ready for immediate animation. The techniques are all specially designed to account for the presence of deterministic signals (harmonics) in case of rotating structural parts.
ARTeMIS Modal also includes up to five time domain modal analysis techniques. They are all of the data driven Stochastic Subspace Identification (SSI) type and are all implementing the powerful Crystal Clear SSI® realization estimator. Crystal Clear SSI® produces extremely clear stabilization diagrams with un-seen accuracy of the physical parameters and nearly no noise modes. The SSI techniques available are:
These techniques estimate the modal parameters directly from the raw measured time series. The SSI techniques incorporate effective ways of dealing with noise. As a result, the modal parameter estimations are the most accurate commercially available today. The SSI techniques can work with closely space and repeated modes with light or heavy damping.
Since the SSI techniques are working in time domain there are no leakage bias or lack of frequency resolution. As a result, the modal parameter estimates are asymptotically unbiased. Further, as the SSI techniques are low model order estimators, the statistical errors of the modal parameter estimates are extremely small.
Test Geometry:
Internal Data Acquisition Module
Frequency Domain Decompostion Techniques:
Stochastic Subspace Identification Techniques:
Mode Validation:
Choosing the right licensing option depends on your organization's needs, budget, and long-term plans. Below are the advantages of each type to help you decide:
Feel free to contact us for guidance or a tailored recommendation.
Contact us at sales@svibs.com for more information or assistance.
Operational Modal Analysis using ARTeMIS Modal
September 2023