Konstantin Busov^1,*, Nikolay Mazheiko¹, Leonid Plotnikov², Boris Zhilkin²

Frontiers in Heat and Mass Transfer, Vol.23, No.4, pp. 1203-1214, 2025, DOI:10.32604/fhmt.2025.067598 - 29 August 2025

Abstract Experimental research into the boiling-up of a free jet of superheated water discharging through a short cylindrical nozzle with sharp inlet and outlet edges into the atmosphere has been carried out. The change in the shape of a liquid jet has been traced through changes in thermodynamic parameters (temperature, pressure) along the saturation line in both the visible range and the infrared spectrum. The flow shapes corresponding to various modes of boiling-up have been identified. With thermal-imaging diagnostics, heterogeneities in the spray plume of a superheated liquid jet have been recorded and temperature distributions have More >

Pratik Jadhav¹, Vuppala Adithya Sairam¹, Niranjan Bhojane¹, Abhyuday Singh¹, Shilpa Gite^1,2, Biswajeet Pradhan^3,*, Mrinal Bachute¹, Abdullah Alamri⁴

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3493-3517, 2025, DOI:10.32604/cmc.2025.060764 - 16 April 2025

Abstract Electronic nose and thermal images are effective ways to diagnose the presence of gases in real-time real-time. Multimodal fusion of these modalities can result in the development of highly accurate diagnostic systems. The low-cost thermal imaging software produces low-resolution thermal images in grayscale format, hence necessitating methods for improving the resolution and colorizing the images. The objective of this paper is to develop and train a super-resolution generative adversarial network for improving the resolution of the thermal images, followed by a sparse autoencoder for colorization of thermal images and a multimodal convolutional neural network for… More >

Hong Zhang^1,*, Qi Wang¹, Lixing Chen¹, Jiaming Zhou¹, Haijian Shao²

Energy Engineering, Vol.120, No.8, pp. 1867-1883, 2023, DOI:10.32604/ee.2023.028453 - 05 June 2023

Abstract Induction motors (IMs) typically fail due to the rate of stator short-circuits. Because of the similarity of the thermal images produced by various instances of short-circuit and the minor interclass distinctions between categories, non-destructive fault detection is universally perceived as a difficult issue. This paper adopts the deep learning model combined with feature fusion methods based on the image’s low-level features with higher resolution and more position and details and high-level features with more semantic information to develop a high-accuracy classification-detection approach for the fault diagnosis of IMs. Based on the publicly available thermal images More > Graphic Abstract

A. Sriram^1,*, T. D. Sudhakar²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2761-2772, 2023, DOI:10.32604/csse.2023.028559 - 21 December 2022

Abstract Intended for good productivity and perfect operation of the solar power grid a failure-free system is required. Therefore, thermal image processing with the thermal camera is the latest non-invasive (without manual contact) type fault identification technique which may give good precision in all aspects. The soiling issue, which is major productivity affecting factor may import from several reasons such as dust on the wind, bird mucks, etc. The efficient power production sufferers due to accumulated soil deposits reaching from 1%–7% in the county, such as India, to more than 25% in middle-east countries country, such… More >

R. Vidhya^1,*, P. Vanaja Ranjan², N. R. Shanker³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 153-168, 2023, DOI:10.32604/iasc.2023.031942 - 29 September 2022

Abstract Preventive maintenance in the transformer is performed through a differential relay protection system, and it protects the transformer from internal and external faults. However, the Current Transformer (CT) in the differential protection system mal-operates during inrush currents. CT saturates due to magnetizing inrush currents and causes false tripping of the differential relays. Moreover, identification of tripping in protection relay either due to inrush current or internal faults needs to be diagnosed. For the above problem, continuous monitoring of transformer breather and CT terminals with thermal camera helps detect the tripping in relay due to inrush More >

Ritam Sharma¹, Janki Ballabh Sharma¹, Ranjan Maheshwari¹, Praveen Agarwal^2,3,4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 923-947, 2022, DOI:10.32604/cmes.2022.016065 - 13 December 2021

Abstract In this paper, a novel hybrid texture feature set and fractional derivative filter-based breast cancer detection model is introduced. This paper also introduces the application of a histogram of linear bipolar pattern features (HLBP) for breast thermogram classification. Initially, breast tissues are separated by masking operation and filtered by Grmwald–Letnikov fractional derivative-based Sobel mask to enhance the texture and rectify the noise. A novel hybrid feature set using HLBP and other statistical feature sets is derived and reduced by principal component analysis. Radial basis function kernel-based support vector machine is employed for detecting the abnormality… More >

Pingping Yu¹, Jiayu Wang¹, Ning Cao^2,*, Heiner Dintera³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3861-3876, 2021, DOI:10.32604/cmc.2021.017527 - 06 May 2021

Abstract Along with the rapid development of biometric authentication technology, face recognition has been commercially used in many industries in recent years. However, it cannot be ignored that face recognition-based authentication techniques can be easily spoofed using various types of attacks such photographs, videos or forged 3D masks. In order to solve this problem, this work proposed a face anti-fraud algorithm based on the fusion of thermal infrared images and visible light images. The normal temperature distribution of the human face is stable and characteristic, and the important physiological information of the human body can be… More >

KRISHAN KUMAR PATEL, RAJESH PUROHIT

Journal of Polymer Materials, Vol.36, No.1, pp. 23-37, 2019, DOI:10.32381/JPM.2019.36.01.3

Abstract Microwave (MV)-induced thermo-responsive shape memory thermoplastic polyurethane (SMTPU)/ MWCNT composites were prepared in micro-compounder. Composites containing different amount of multiwall Carbon nanotube (MWCNT) varying from 0 to 1.5 phr in SMTPU matrix were prepared. Maximum stretching strength, recovery force and tensile strength for 1.5 CNTPU (1.5 phr MWCNT in SMTPU matrix) was increased by 120%, 100% and 24% respectively as compared to SMTPU. MV-induced shape memory is a novel approach for fast, clean and remote heating during operation. MWCNT is strong absorber of microwave irradiation so that SMTPU/ MWCNTs nanocomposites successfully triggered by microwave. More >