FDD
Frequency Domain Decomposition uses singular-value decomposition of the cross-spectral matrix to identify spectral peaks and mode shapes.
Brincker · Zhang · Andersen
The engine library
FDD and SSI
identification methods.
Estimate modal frequencies, damping ratios, and mode shapes from ambient vibration measurements. Compare candidates and review diagnostics before accepting results.
0FD
Frequency-domain engines, FDD through the AFDD wizard.
0TD
Current time-domain engines: three SSI variants.
0SPECTRUM
Interrogable spectral tools on the bench beneath the engines.
0GATE
One commit gate; one authoritative set of identified modes.
Frequency domain
Frequency-domain methods.
Core includes FDD and EFDD. Pro and Ultimate add FSDD and CFDD. The peak wizard supports guided candidate selection; method descriptions below explain the differences.
EFDD
Enhanced FDD isolates a spectral bell around a selected peak and uses correlation decay to estimate frequency and damping.
Brincker · VenturaFSDD
Frequency-Spatial Domain Decomposition applies spatial filtering during modal identification.
Zhang et al.CFDD
Curve-fit FDD fits a single-degree-of-freedom model in the frequency domain to estimate damping.
Jacobsen · AndersenAFDD Peak Wizard
Guided peak selection using modal coherence scores, with candidates available for review.
Modal-coherence criterion
Time domain
Stochastic subspace
Stochastic subspace
identification.
Core includes SSI-COV. Pro and Ultimate add SSI-DATA, the UPC/PC/CVA weighting options, and SSI-UPCX uncertainty estimates.
SSI-COV
Covariance-driven SSI estimates a state-space model from response covariances. Stabilization diagrams support candidate review across model orders.
Van Overschee · De MoorSSI-DATA
Data-driven SSI uses orthogonal projection of measurement data to estimate the state-space model.
Peeters · De RoeckSSI-UPCX
SSI-UPCX reports conditional frequency and damping uncertainty from sensitivity propagation under a fixed-observability residual model. Descriptive scatter across fitted models is reported separately. Full SSI sampling coverage is not established.
Method family — Döhler · MevelPrepare and inspect the input signals before selecting a method. Signal preparation and spectral tools →
Validation battery
Modal diagnostics.
Use correlation, stabilization, complexity, and contamination checks to assess candidates. Advanced validation tools and SSI uncertainty estimates require Pro or Ultimate.
MACModal Assurance Criterion matrices across the full identified set.
CrossMACCross-method shape correlation across the current FDD and SSI families.
MPC · MPDModal phase collinearity and mean phase deviation for complexity screening.
StabilizationMulti-order stabilization diagrams with stability and heuristic quality screens.
Harmonic screeningInspect periodic-line contamination before interpreting damping.
Aliasing riskPer-mode aliasing exposure assessed against the acquisition chain.
Mode qualityQuality indicators help prioritize candidate review.
σ evidenceConditional frequency and damping uncertainty, with separately labeled family scatter in review and reports.
Damping cross-validation
Damping cross-checks.
Half-power bandwidth and CFDD fitting provide the current automatic damping cross-checks. The estimator that supplied the committed value is excluded from its own comparison. Disagreement is shown for review. Damping checks in Deep Estimate →
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