estimate_rul
Estimates remaining useful life by analyzing a degradation signal, extracting features, and fitting a curve to predict when failure threshold will be reached.
Instructions
Estimate Remaining Useful Life from a degradation signal.
Segments the signal, extracts a feature series (e.g. RMS over time),
and fits a degradation curve to estimate when *failure_threshold*
will be reached.
Args:
ctx: MCP context for user communication.
signal_file: CSV signal file in the data directory.
failure_threshold: Feature value at which the component is
considered failed.
method: Estimation method — "linear", "exponential", "weibull",
or "kalman" (default: "linear").
feature_name: Time-domain feature to track (default: "rms").
sampling_interval: Time between successive segments in the
units you want the RUL expressed in (default: 1.0).
sampling_rate: Signal sampling rate in Hz (auto-detect if None).
segment_duration: Duration of each segment in seconds.
overlap_ratio: Overlap between segments (0-1).
Returns:
RULEstimationResult with estimated RUL and confidence.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| signal_file | Yes | ||
| failure_threshold | Yes | ||
| method | No | linear | |
| feature_name | No | rms | |
| sampling_interval | No | ||
| sampling_rate | No | ||
| segment_duration | No | ||
| overlap_ratio | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| rul | Yes | Estimated remaining useful life in time units | |
| confidence | Yes | R-squared or confidence metric (0-1) | |
| method | Yes | Estimation method used | |
| confidence_interval | No | [lower, upper] RUL bounds (Kalman only) | |
| shape | No | Weibull shape parameter (Weibull only) | |
| scale | No | Weibull scale parameter (Weibull only) | |
| estimated_rate | No | Estimated degradation rate (Kalman only) |