The turbine blade is a key component in an aeroengine. Currently, measuring the turbine blade radiation temperature always requires obtaining the emissivity of the target surface in advance. However, changes in the emissivity and the reflected ambient radiation cause large errors in measurement results. In this paper, a three-wavelength radiation temperature measurement method was developed, without known emissivity, for reflection correction. Firstly, a three-dimensional dynamic reflection model of the turbine blade was established to describe the ambient radiation of the target blade based on the real surface of the engine turbine blade. Secondly, based on the reflection correction model, a three-wavelength radiation temperature measurement algorithm, independent of surface emissivity, was proposed to improve the measurement accuracy of the turbine blade radiation temperature in the engine. Finally, an experimental platform was built to verify the temperature measurement method. Compared with three conventional colorimetric methods, this method achieved an improved performance on blade temperature measurement, demonstrating a decline in the maximum error from 6.09% to 2.13% and in the average error from 2.82% to 1.20%. The proposed method would benefit the accuracy in the high-temperature measurement of turbine blades.

Infrared imaging spectrometry is utilized to detect and identify targets by collecting spectral images. In some cases, the infrared spectral images of dynamic targets need to be detected accurately, such as during remote sensing target tracking and engine tail flame detection applications. However, it is difficult to obtain reliable measurement results when using a traditional infrared imaging spectrometer with a scanning structure because of motion artifacts. This work proposes a snapshot infrared imaging Fourier transform spectrometer (SIIFTS) based on stepped micromirrors and a lens array. Two micromirrors sample the spectral information, and the lens array can realize multi-aperture snapshot imaging. The spectrometer is capable of collecting three-dimensional (3D) datasets during a single measurement period, and its absence of motion artifacts and its ability to work without moving parts is very important for dynamic target detection. The achromatic optical design of the SIIFTS is completed, and two front imaging systems for remote sensing and tail flame detection applications are designed for selection. A SIIFTS prototype was built, and flame detection tests were conducted in a laboratory environment. The experimental results show that the SIIFTS developed here can accurately and stably obtain real-time image and spectral information from dynamic targets.

Endoscopic inspection is an important non-destructive testing method. Traditional 3D endoscopic reconstruction methods, such as polarization reconstruction and shading reconstruction, have the drawbacks of not determining the object’s actual size and positional information. The stereo vision method is limited by its operating principles and has the issue of sparse reconstructed point clouds. These drawbacks greatly restrict the applications of the endoscope. Therefore, this work proposes a joint dense 3D reconstruction method for endoscopic images of weak texture scenes. This method uses the shading reconstruction normal to correct the polarization reconstruction normal, then uses coordinate conversion and point cloud fusion to convert the polarization and shading 3D reconstruction results from the pixel coordinate system to the world coordinate system. Finally combines the reconstruction results from the world coordinate system’s polarization, shading, and stereo vision. The fusion coefficients are obtained by solving the minimum error model, and then a complete and detailed 3D reconstruction surface was obtained in the world coordinate system. This method could avoid the difficulty of obtaining real coordinates for the 3D reconstruction of polarization and shading and prevent the issue of the sparse point cloud afforded by stereo vision reconstruction for weak texture scenes. The combined dense 3D reconstruction method had an average error of < 1% for length measurement of a 3D curve, which is highly significance for industrial endoscopic inspection.

In recent years, various fields have established an urgent need for real-time online measurement of infrared spectra. To this end, reducing the weight and size of infrared spectrometers is particularly important. This paper reports a micro-optical element static Fourier transform spectrometer (MOESFTS) with a working wavelength from $3.7~\mu \text{m}$ to $4.8~\mu \text{m}$ . This spectrometer is entirely composed of micro-optical elements, and its interference system comprises stepped micromirrors and a lightweight beam splitter to realize a lightweight, miniaturized instrument capable of static real-time spectrum measurements. The micro-optical element microlens array leads to the acquisition of interferogram in the form of two-dimensional point-array in the MOESFTS. Therefore we establish a field-of-view integral model of the interference-image point intensity to analyze the influence of the field of view on the reconstructed spectrum. We complete the optical design of the micro-optical collimator (MOC) lens and the micro-optical relay (MOR) lens. And an effective processing algorithm for spectral reconstruction from two-dimensional point-array is presented. A prototype was designed and constructed, and spectral calibration was completed. The spectra of acetonitrile (CH ₃ CN) and carbon dioxide (CO ₂ ) were measured, the experimental results show that the spectral peak drift errors were found to be less than 0.18%.