failure_prediction

failure_prediction

FailurePredictionEvents

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

Bases: Base

Predict remaining useful life and detect escalating failure patterns in time series signals from manufacturing/industrial IoT systems.

remaining_useful_life

remaining_useful_life(
    degradation_rate: float, failure_threshold: float
) -> pd.DataFrame

Estimate remaining useful life (RUL) at each point via linear extrapolation from the recent trend to a failure threshold.

Parameters:

Name	Type	Description	Default
degradation_rate	float	Expected rate of change per second (used as fallback if local slope cannot be computed).	required
failure_threshold	float	The signal level that represents failure.	required

Returns:

Type	Description
DataFrame	DataFrame with columns: systime, uuid, is_delta, current_value,
DataFrame	rul_seconds, rul_hours, confidence.

detect_exceedance_pattern

detect_exceedance_pattern(
    warning_threshold: float,
    critical_threshold: float,
    window: str = "1h",
) -> pd.DataFrame

Track frequency of threshold exceedances in rolling windows and flag escalating patterns (increasing exceedance counts).

Parameters:

Name	Type	Description	Default
warning_threshold	float	Warning level (absolute value comparison).	required
critical_threshold	float	Critical level (absolute value comparison).	required
window	str	Rolling window size.	'1h'

Returns:

Type	Description
DataFrame	DataFrame with columns: window_start, uuid, is_delta,
DataFrame	warning_count, critical_count, escalation_detected.

time_to_threshold

time_to_threshold(
    threshold: float, direction: str = "increasing"
) -> pd.DataFrame

Estimate time to reach a threshold based on recent rate of change.

Parameters:

Name	Type	Description	Default
threshold	float	Target threshold value.	required
direction	str	'increasing' or 'decreasing'.	'increasing'

Returns:

Type	Description
DataFrame	DataFrame with columns: systime, uuid, is_delta, current_value,
DataFrame	rate_of_change, estimated_time_seconds.