vibration_analysis

vibration_analysis ¤

VibrationAnalysisEvents ¤

VibrationAnalysisEvents(
    dataframe: DataFrame,
    signal_uuid: str,
    *,
    event_uuid: str = "maint:vibration",
    value_column: str = "value_double",
    time_column: str = "systime"
)

Bases: Base

Analyse vibration signals from industrial equipment: RMS exceedance, amplitude growth, and bearing health indicators (kurtosis, crest factor).

detect_rms_exceedance ¤

detect_rms_exceedance(
    baseline_rms: float,
    threshold_factor: float = 1.5,
    window: str = "1m",
) -> pd.DataFrame

Compute rolling RMS and flag intervals exceeding baseline_rms * threshold_factor.

Parameters:

Name	Type	Description	Default
`baseline_rms`	`float`	Known baseline RMS value for healthy equipment.	required
`threshold_factor`	`float`	Multiplier above baseline to trigger alarm.	`1.5`
`window`	`str`	Rolling window size.	`'1m'`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: start, end, uuid, is_delta,
`DataFrame`	rms_value, baseline_rms, ratio, duration_seconds.

detect_amplitude_growth ¤

detect_amplitude_growth(
    window: str = "1h", growth_threshold: float = 0.1
) -> pd.DataFrame

Track peak-to-peak amplitude in non-overlapping windows and flag windows where amplitude grows beyond growth_threshold relative to baseline.

Parameters:

Name	Type	Description	Default
`window`	`str`	Window size for amplitude measurement.	`'1h'`
`growth_threshold`	`float`	Minimum fractional growth (e.g. 0.1 = 10%) to flag.	`0.1`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: window_start, uuid, is_delta,
`DataFrame`	amplitude, baseline_amplitude, growth_pct.

bearing_health_indicators ¤

bearing_health_indicators(
    window: str = "5m",
) -> pd.DataFrame

Compute bearing health indicators per window: RMS, peak value, crest factor (peak/RMS), and kurtosis.

Parameters:

Name	Type	Description	Default
`window`	`str`	Window size for indicator computation.	`'5m'`

Returns:

Type	Description
`DataFrame`	DataFrame with columns: window_start, uuid, is_delta,
`DataFrame`	rms, peak, crest_factor, kurtosis.