Which fault condition is easier to diagnose by using time waveform analysis instead of spectrum analysis alone?

In the context of vibration analysis, time waveform analysis is particularly effective for diagnosing certain fault conditions due to its ability to capture the transient events and non-sinusoidal waveforms that are characteristic of specific mechanical issues.

A broken gear tooth presents a clear example where time waveform analysis excels. When a gear experiences a tooth failure, the resulting vibrations can produce distinct impacts or spikes in the time domain signal. This impact creates a waveform that is easily identifiable, as it may exhibit sharp, high-frequency transient spikes corresponding to the moment the broken tooth fails to engage properly with the mating gear.

While spectrum analysis can certainly help identify the frequency content of vibrations, it may not clearly indicate the sudden, impulsive nature of the fault, particularly if the frequency of the fault lies within a noise-rich environment. The time waveform analysis captures the actual pattern of impact forces over time, allowing for a more straightforward identification of the broken tooth condition.

In contrast, other conditions like misalignment, cavitation, and unbalance may show patterns in spectrum analysis that are more nuanced or gradual, thus making detection of those issues less reliant on the time domain data. Misalignment often manifests as sidebands around the fundamental frequency, while cavitation may have specific frequency patterns that could be better