Technical basis and risk boundary of infrared imaging project

Main risks and boundaries

1. The pseudo-color image is not temperature data. Colors are generated from the color palette and current range, and the same color may represent different temperatures in different images.
2. Ordinary thermal imaging does not automatically equal radiation thermometry. It is necessary to confirm whether the camera outputs radiometric data, calibration range and error conditions.
3. Surface temperature is not equal to internal temperature. Battery core temperature, food core temperature, grain pile deep temperature and human core body temperature must be verified with corresponding true values.
4. Reflections from metal, glass, water, and smooth surfaces can create false hot spots. Low emissivity targets should be compensated for emissivity and reflected apparent temperature.
5. Thermal images generally cannot see through ordinary glass, walls, clothing, or physical ruins. Visible "heat trails" do not mean visible objects.
6. NIR/SWIR mainly looks at the difference in reflection, transmission or absorption, not the normal temperature temperature chart. Active fill light also evaluates eye safety, uniformity and ambient light.
7. SWIR/Hyperspectral component regression is highly dependent on sample, waveband, light source, temperature and laboratory truth. Independent batch external verification is required.
8. Optical gas imaging must match gas absorption spectra and specialized filters. A visible gas plume does not mean that the gas has been identified, nor does it mean that the concentration or leak rate has been measured.
9. Active thermal NDT defect depth and detection rates are dependent on material, thickness, excitation, sampling, and reference coupons. Composite drawings or individual samples cannot prove POD.
10. AI enhancement and super-resolution may create textures or change borders. The measurement chain should retain the original data and the enhanced plots should not replace the original quantitative results.
11. Medical, firefighting, equipment shutdown, law enforcement, and identification are high-risk uses that require independent regulatory, functional safety, deviation, and human review design.
12. Public data is only suitable for algorithm baseline and reproduction verification, and cannot replace product domain acceptance of target equipment, lenses, installation distances, environments and business processes.

Inputs required to start the project

• Camera brand, model, detector type, spectral band, resolution, pixel size, lens and field of view;
• Whether it is radiation type, output format, bit depth, temperature matrix interface, SDK, range/gain file and NUC mode;
• Whether there is a shutter, blackbody, external temperature reference source, infrared window and sync/trigger interface;
• Target material, emissivity, surface condition, temperature range, distance, minimum target size and desired number of pixels;
• Ambient temperature, humidity, wind, solar radiation, smoke, rain, fog and background reflection conditions;
• Still images, continuous video, timestamps, equipment loads, process volumes and asset/part identification;
• If it is dual light: internal and external parameters, time synchronization, resolution, focal length, field of view and installation stiffness of the two cameras;
• If it is SWIR/hyperspectral: light source, white board, dark field, wavelength calibration, sample batch and laboratory true value;
• If it is active thermal imaging: excitation type, power/timing, camera frame rate, sample material thickness and artificial defects;
• If it is OGI: target gas, special filter spectrum segment, true flow value, wind speed, distance and background temperature difference;
• If human/animal: ethics, consent, environmental stabilization time, ROI protocols, clinical/veterinary truth and data retention;
• Written acceptance metrics, independent test sets, failure conditions, manual review processes, and linkage boundaries.

Public technical information

The following materials illustrate engineering conditions, measurement influencing factors, public data, and industry methodologies. Specific project indicators are based on target equipment, project data and test results under on-site conditions.

Rules for the use of evidence

Indicators involving performance, accuracy, frame rate, distance, detection rate or stability should also record the target device, data range, environment, version, statistical caliber and review results.