[DAQmx Read] → (Raw Vibration Signal) ↓ [Wavelet Denoise.vi] (db8, level 4, soft threshold, SURE) ↓ [STFT Spectrogram.vi] (window length 256, overlap 128) ↓ [Peak Detector.vi] (locate fault frequency harmonics) ↓ [Pattern Match.vi] (compare to theoretical bearing frequencies) ↓ [User Indicator: Fault Severity]
This report is accurate as of LabVIEW 2024 Q3 / ASP Toolkit version 21.0. For the latest NI documentation, refer to NI Advanced Signal Processing Toolkit Manual (part number 374527C-01). labview advanced signal processing toolkit
Analyzing ECG or EEG signals often requires distinguishing between normal rhythmic activity and transient anomalies. Wavelet analysis within the toolkit is specifically tuned for detecting these "events" (like a spike in brain activity) within a noisy background. [DAQmx Read] → (Raw Vibration Signal) ↓ [Wavelet Denoise
A bearing fault produces a non-stationary impulse train. The STFT (spectrogram) VIs in the toolkit can reveal sidebands around the ball pass frequency that are invisible in a standard power spectrum. Wavelet analysis within the toolkit is specifically tuned
The LabVIEW Advanced Signal Processing Toolkit is a for engineers dealing with non-stationary signals in hardware-in-the-loop or real-time test systems. Its strengths are seamless NI hardware integration, deterministic execution for most algorithms (excluding subspace methods), and a graphical approach that reduces coding errors.