Application of active thermography in study of the rotors dynamics

The article presents the infrared measurement techniques for analyzing and monitoring the dynamic state of the structure using advanced thermal imaging techniques. The article present an overview of the infrared measurement techniques and algorithms proposed research design based on the selected infrared measurement techniques. The article presents the results of a series of studies on the possibility of applying the vibrothermography methods in SHM systems. In particular it focuses on the analysis of the possibility of studying the dynamics of the rotor and the detection of its failures during operation. The results of vibrothermography studies of impeller made of plastic are presented. The results of studies based on algorithms developed by the authors. The article also presents the concept of the use of thermal imaging research in fault detection and monitoring of the dynamic state of real objects.

Improving Quality Inspection of Textiles by an Augmented RGB-IR-HS-AI Approach

The aim of this research topic and paper is to investigate the application possibilities of vision technology in the textile industry. These include RGB, active thermography and hyperspectral imaging techniques. In the future, this approach will be supplemented by a machine learning algorithm (e.g., in Matlab or Python) to enable the detection of defects in textiles and to correctly categorize these defects. In the first place, the various options for building such a convolutional neural network are discussed. The focus was on the models used in the literature. Based on the effectiveness of these ML models and the feasibility to build them, choices can be made to determine the most suitable models. Sufficient samples are an important link to properly train a model. Because there is a shortage of open data, it is also discussed how samples obtained from the textile industry, were measured in the lab. At first, we will limit ourselves to the five most common defects. In a later phase of research, the results with this dataset and the open datasets are benchmarked against the results from the literature.

Evaluation of Effectiveness of Heat Treatments in Boron Steel by Laser Thermography

The applicability of active thermography as a non-destructive method to distinguish heat treated from not-treated boron steel has been investigated. While the usual hardness semi-destructive tests influence the inspected surface, laser thermography is capable of verifying the effectiveness of heat treatment in boron steel in a non-destructive way without any surface modification. The procedure has been verified on two plates of boron steels with different structures (100% ferritic–pearlitic and 100% martensitic).

A Physics-Informed Neural Network Method for Defect Identification in Polymer Composites Based on Pulsed Thermography

Defect detection in composite materials using active thermography is a well-studied field, and many thermographic data analysis methods have been proposed to facilitate defect visibility enhancement. In this work, we introduce a deep learning method that is constrained by known heat transfer phenomena described by a series of governing equations, also known in the literature as the physics-informed neural network (PINN). The accurate reconstruction of background information based on thermal images facilitates the identification of subsurface defects and reduction in noises caused by an uneven background and heating. The authors illustrate the method’s feasibility through experimental results obtained after pulsed thermography (PT) on a carbon fiber-reinforced polymer (CFRP) specimen.

Estimating Thermal Material Properties Using Step-Heating Thermography Methods in a Solar Loading Thermography Setup

This work investigates solar loading thermography applications using active thermography algorithms. It is shown that active thermography methods, such as step-heating thermography, present good correlation with a solar loading setup. Solar loading thermography is an approach that has recently gained scientific attention and is advantageous because it is particularly easy to set up and can measure large-scale objects, as the sun is the primary heat source. This work also introduces the concept of using a pyranometer as a reference for the evaluation algorithms by providing a direct solar irradiance measurement. Furthermore, a recently introduced method of estimating thermal effusivity is evaluated on ambient-derived thermograms.