L1 ⚛ L1-115 ⊙ Testnet

Active Thermography (pulsed / lock-in IR inspection)

Industrial Inspection · Thermal-diffusion non-destructive imaging

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⬇ L1-115.md

# ⚛ L1 Principle — Active Thermography (pulsed / lock-in IR inspection) **ID:** `L1-115` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Industrial Inspection — *Thermal-diffusion non-destructive imaging* > **🎯 Problem class:** nonlinear inverse · **🧮 Solution space:** 3D defect depth map > **📡 Carrier:** photon · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554200 --- ## 🧠 1. Introduction **Active Thermography (pulsed / lock-in IR inspection)** is a **nonlinear inverse problem** whose unknown lives in **3D defect depth map** space, within the **Thermal-diffusion non-destructive imaging** sub-domain of **Industrial Inspection**. Measurements consist of photons collected by an optical detector via a **active thermography ir** sensing mechanism. The forward operator applies, in order: L · heat source operator; L · thermal diffusion operator; D · ir camera operator; detector accumulates flux over the exposure window. Observations are corrupted by additive Gaussian noise. Existence of the recovered 3D defect depth map is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 12); emissivity_variation dominates the stability cliff; surface_reflections and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. ## ⚙ 2. Forward Model Physical chain: **x** → L · heat source → L · thermal diffusion → D · ir camera → Temporal integration → **y** (detector). ``` y = ∫_t dt `D.ir_camera` `L.thermal_diffusion` `L.heat_source` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.heat_source` | L · heat source operator | | `L.thermal_diffusion` | L · thermal diffusion operator | | `D.ir_camera` | D · ir camera operator | | `int.temporal` | Detector accumulates flux over the exposure window | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Industrial Inspection | | Sub domain | Thermal-diffusion non-destructive imaging | | Carrier | photon | | Problem class | nonlinear_inverse | | Solution space | 3D_defect_depth_map | | Noise model | gaussian | | Integration axis | temporal | | Difficulty delta | 3 | | L dag | 3 | ## 📡 4. Measurement Model Existence of the recovered 3D defect depth map is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 12); emissivity_variation dominates the stability cliff; surface_reflections and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. | Metric | Value | |---|---| | Metric | PSNR_dB | | Secondary | SSIM | ## 📏 5. Operating Range (Ω) **Center problem class:** `active_thermography` · **Forward operator:** `active_thermography_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 640 | | W | px | 480 | | Snr db | dB | 25 | | N frames | — | 200 | | F lockin hz | Hz | 1 | | Surface reflections | — | 0 | | Ambient thermal load | — | 0 | | Emissivity variation | — | 0.05 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 128 – 2048 | | W | px | 128 – 2048 | | Snr db | dB | 0.0 – 40.0 | | N frames | — | 30 – 2000 | | F lockin hz | Hz | 0.01 – 100 | | Convective losses | — | 0.0 – 0.3 | | Surface reflections | — | 0.0 – 0.3 | | Ambient thermal load | — | 0.0 – 0.2 | | Emissivity variation | — | 0.0 – 0.3 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 23.0 | Metric | Range | |---|---| | Psnr db | 5.0 – 40.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `240` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xcabe36d7ec648dc8b250bf87a26c8dd9db0b75eff4b2d22474364282589ad5fa` - **Chain tx hash:** `0x3bf42c3ca3d4eff9e93cbfe90337a0aab0baad99ce025fd19eb9a24238dd713b` - **Chain block:** `41554200` --- ## File Mapping This bundle consists of: `L1-115.md`, `L1-115.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-115.md` | Source of truth — edit this | Human or LLM | | `L1-115.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-115`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-115.md).
Regenerate L1-115.json so every field matches the Markdown.
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L2-115-001 Active Thermography (pulsed / lock-in IR inspection) Mismatch-Only Spec

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📋 JSON metadata

{
  "artifact_id": "L1-115",
  "chain_block": 41554200,
  "chain_hash": "0xcabe36d7ec648dc8b250bf87a26c8dd9db0b75eff4b2d22474364282589ad5fa",
  "chain_tx_hash": "0x3bf42c3ca3d4eff9e93cbfe90337a0aab0baad99ce025fd19eb9a24238dd713b",
  "domain": "Industrial Inspection",
  "hardness_fn": {
    "delta": 3,
    "kappa": 240,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "PSNR_dB",
    "regime": "Existence of the recovered 3D defect depth map is guaranteed within the declared Omega bounds. Uniqueness is local rather than global (non-convex landscape); convergence depends on initialisation and priors. Stability is moderately conditioned (kappa_eff ~= 12); emissivity_variation dominates the stability cliff; surface_reflections and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point.",
    "secondary": "SSIM"
  },
  "physics_fingerprint": {
    "L_DAG": 3.0,
    "carrier": "photon",
    "difficulty_delta": 3,
    "domain": "Industrial Inspection",
    "integration_axis": "temporal",
    "noise_model": "gaussian",
    "primitives": [
      "L.heat_source",
      "L.thermal_diffusion",
      "D.ir_camera",
      "int.temporal"
    ],
    "problem_class": "nonlinear_inverse",
    "sensing_mechanism": "active_thermography_ir",
    "solution_space": "3D_defect_depth_map",
    "sub_domain": "Thermal-diffusion non-destructive imaging",
    "title": "Active Thermography (pulsed / lock-in IR inspection)"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "active_thermography_forward"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "N_frames",
      "f_lockin_Hz",
      "SNR_dB",
      "emissivity_variation",
      "surface_reflections",
      "ambient_thermal_load",
      "emissivity_variation",
      "surface_reflections",
      "ambient_thermal_load",
      "convective_losses"
    ],
    "allowed_problem_classes": [
      "active_thermography"
    ],
    "center_spec": {
      "epsilon_fn_center": "23.0",
      "forward_operator": "active_thermography_forward",
      "input_format": "measurement_only",
      "omega": {
        "H": 640,
        "N_frames": 200,
        "SNR_dB": 25,
        "W": 480,
        "ambient_thermal_load": 0.0,
        "emissivity_variation": 0.05,
        "f_lockin_Hz": 1,
        "surface_reflections": 0.0
      },
      "problem_class": "active_thermography"
    },
    "epsilon_bounds": {
      "psnr_db": [
        5.0,
        40.0
      ]
    },
    "omega_bounds": {
      "H": [
        128,
        2048
      ],
      "N_frames": [
        30,
        2000
      ],
      "SNR_dB": [
        0.0,
        40.0
      ],
      "W": [
        128,
        2048
      ],
      "ambient_thermal_load": [
        0.0,
        0.2
      ],
      "convective_losses": [
        0.0,
        0.3
      ],
      "emissivity_variation": [
        0.0,
        0.3
      ],
      "f_lockin_Hz": [
        0.01,
        100
      ],
      "surface_reflections": [
        0.0,
        0.3
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Thermal-diffusion non-destructive imaging",
  "title": "Active Thermography (pulsed / lock-in IR inspection)"
}

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