Time Waveform Analysis
Time Waveform Analysis (TWA) is the examination of the raw, unprocessed vibration signal (acceleration, velocity, or displacement) plotted against time, capturing the exact physical motion of a machine component moment-to-moment before mathematical transformation into the frequency domain (FFT). It reveals transient events, impacts, modulation, and non-stationary behaviors that are often averaged out or obscured in standard spectral analysis.
In shop floor maintenance, TWA is used to diagnose low-speed machinery (<100 RPM) where FFT resolution is insufficient, assess rolling element bearing defect severity by capturing true peak amplitudes of impact events, and analyze gear faults such as broken teeth showing repetitive shock pulses at 1X revolution. It is critical for detecting cavitation, rubs, looseness, and beats, and is applied in sleeve bearing machines with X-Y probes for orbit analysis. In CMMS/ServiceGrid, TWA data is stored as a baseline for pattern recognition to compare current survey data against historical readings for anomaly detection.
- Averaging out impacts: Using standard FFT averaging on machines with impacts (e.g., bearings, gears) smooths out the 'clicks' and 'pops' that indicate early failure, leading to missed diagnoses.
- Incorrect instrument setup: Failing to set the correct sampling rate and total sample period results in aliasing or missing critical transient events, rendering the waveform useless.
- Routine over-collection: Collecting TWA on every measurement location regularly without need drastically increases data storage requirements and analysis time without adding value.
How does TWA differ from FFT in diagnosing a broken gear tooth?
FFT shows frequency peaks at gear mesh frequency, but TWA reveals the repetitive shock pulse occurring once per revolution (1X), providing direct visual confirmation of the impact and its severity.
What are the two main parameters for setting up a time waveform measurement?
The total sample period (duration) and the sampling rate (frequency), which must be calculated based on the target maximum frequency (Fmax) and shaft speed to ensure adequate resolution.
Why is TWA superior for low-speed machines?
At speeds <100 RPM, FFT requires extremely long acquisition times to achieve sufficient frequency resolution; TWA captures the raw transient impacts directly, bypassing these resolution limitations.