twinnable-weights / model_metadata_v9c.json
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{
"version": "v9c",
"sprint": "A7c",
"trained_at": "2026-03-28T17:30:02.968878+00:00",
"backbone_source": "v8 (frozen \u2014 CMAPSS+SCANIA heads unchanged)",
"vsn_rho_method": "perturbation_sensitivity",
"domains": {
"cmapss": {
"rul_source": "supervised",
"onnx": "tft_weights_v8_cmapss.onnx",
"note": "Unchanged from v8"
},
"scania": {
"rul_source": "supervised",
"onnx": "tft_weights_v8_scania.onnx",
"note": "Unchanged from v8"
},
"nist": {
"rul_source": "synthetic_estimated",
"onnx": "tft_weights_v9c_nist.onnx",
"auc": 0.9276,
"rmse": 0.6232,
"vsn_rho": 0.5868,
"vsn_validated": false,
"nist_seed": 42
},
"femto": {
"rul_source": "supervised",
"onnx": "tft_weights_v10a_femto.onnx",
"rmse_cycles": 78.5705,
"rmse_normalised": 0.2568,
"mae_cycles": 39.7257,
"r2": -0.0452,
"vsn_rho": 0.1341,
"vsn_validated": false,
"rul_cap": 306,
"n_features": 14,
"feature_names": [
"H_rms",
"H_kurt",
"H_peak",
"H_crest",
"H_skew",
"H_shape",
"H_impulse",
"V_rms",
"V_kurt",
"V_peak",
"V_crest",
"V_skew",
"V_shape",
"V_impulse"
],
"backbone_frozen": true,
"backbone_version": "v9c",
"fpt_method": "H_rms > mean+3.0\u03c3 (healthy_pct=0.1)"
},
"nist_anomaly": {
"rul_source": "none",
"head_type": "anomaly_only",
"onnx": "tft_weights_v11a_nist_anomaly.onnx",
"auc": 0.9216,
"vsn_rho": 0.5692,
"auc_validated": true,
"n_sensors": 14,
"window_size": 30,
"backbone_frozen": true,
"backbone_version": "v9c",
"training_data": "mds2-2361 nominal (nist_windows_v9c.npz cache)",
"note": "ESTIMATED \u2014 synthetic anomaly labels from A7c cache."
},
"cnc": {
"rul_source": "supervised",
"head_type": "rul_anomaly",
"onnx": "tft_weights_v12a_cnc.onnx",
"scaler": "cnc_scaler_v12a.pkl",
"rmse_um": 36.6639,
"rmse_normalised": 0.2444,
"mae_um": 35.2722,
"r2": -0.4361,
"vsn_rho": 0.3495,
"vsn_validated": false,
"vb_cap": 150.0,
"vb_fpt": 50.0,
"n_features": 14,
"feature_names": [
"mean",
"std",
"rms",
"kurtosis",
"peak",
"crest_factor",
"skewness",
"shape_factor",
"impulse_factor",
"variance",
"peak_to_peak",
"mav",
"zero_crossing_rate",
"waveform_length"
],
"train_cutter": "c4",
"val_cutter": "c6",
"backbone_frozen": true,
"backbone_version": "v9c",
"dataset": "PHM 2010 (C4 train, C6 validate)",
"note": "ESTIMATED if rho < 0.75. C1 not in mirror \u2014 C4/C6 only."
},
"cnc_nuaa": {
"onnx_path": "tft_weights_v15a_cnc_nuaa.onnx",
"scaler_path": "cnc_nuaa_scaler_v15a.pkl",
"rul_cap": 0.3,
"rul_cap_unit": "mm",
"vb_cap_mm": 0.3,
"signals": [
"bending_moment_x",
"bending_moment_y",
"torsion",
"axial_force",
"spindle_power",
"spindle_current"
],
"n_stats": 7,
"seq_len": 5,
"input_dim": 42,
"nrmse": 0.6785,
"r2": -2.0818,
"vsn_rho": 0.0746,
"badge": "ESTIMATED",
"dataset": "NUAA Ideahouse (IEEE DataPort DOI:10.21227/3aa1-5e83)",
"opc_ua_proxy": "bending_moment+torsion+spindle ~ /Nck/Spindle/driveLoad"
}
},
"product_classifier": {
"version": "v1",
"onnx": "product_classifier_v1.onnx",
"scaler": "product_classifier_scaler_v1.pkl",
"labels": "product_classifier_labels_v1.pkl",
"n_features": 14,
"feature_names": [
"Total_running_time_NC_program",
"Tool_number_Magazine_9998_Place_1",
"Spindle_position_error",
"Z-axis_position_MCS",
"X-axis_position_MCS",
"Spindle_angular_velocity",
"Spindle_speed",
"Spindle_smoothed_speed",
"X-axis_position_WCS",
"Z-axis_position_WCS",
"ToolChange_smoothed_current_value",
"ToolChange_smoothed_torque",
"Net_running_time_program",
"Tool_number_Magazine_Place_6"
],
"product_labels": [
1.0,
2.0,
3.0
],
"n_classes": 3,
"window_size": 30,
"conf_threshold": 0.7,
"val_accuracy": 0.9993,
"dataset": "TUAWS (Zenodo 15735480)"
},
"wear_multipliers": {
"version": "v1",
"source": "UC Berkeley Milling Dataset (NASA)",
"method": "linear_regression_VB_vs_run_per_case",
"nominal_condition": "cast_iron_avg",
"nominal_rate_um_per_cut": 0.0512,
"multipliers": {
"1": 1.0,
"2": 2.189,
"3": 2.406
},
"product_mapping": {
"1": "Product A \u2014 nominal (cast iron average)",
"2": "Product B \u2014 steel average (2.189x nominal)",
"3": "Product C \u2014 most aggressive condition (2.406x nominal)"
},
"note": "Derived from UC Berkeley milling dataset. Cast iron = nominal (1.0). Steel = material_2 avg rate / material_1 avg rate. Aggressive = max rate across all conditions / nominal. On a real cell, these would be replaced by calibration runs per product."
}
}