Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography

Monitoring the thermal condition of electrical equipment is necessary for maintaining the reliability of electrical system. The degradation of electrical equipment can cause excessive overheating, which can lead to the eventual failure of the equipment. Additionally, failure of equipment requires a lot of maintenance cost, manpower and can also be catastrophic- causing injuries or even deaths. Therefore, the recognition processof equipment conditions as normal and defective is an essential step towards maintaining reliability and stability of the system. The study introduces infrared thermography based condition monitoring of electrical equipment. Manual analysis of thermal image for detecting defects and classifying the status of equipment take a lot of time, efforts and can also lead to incorrect diagnosis results. An intelligent system that can separate the equipment automatically could help to overcome these problems. This paper discusses an intelligent classification system for the conditions of equipment using neural networks. Three sets of features namely first order histogram based statistical, grey level co-occurrence matrix and component based intensity features are extracted by image analysis, which are used as input data for the neural networks. The multilayered perceptron networks are trained using four different training algorithms namely Resilient back propagation, Bayesian Regulazation, Levenberg–Marquardt and Scale conjugate gradient. The experimental results show that the component based intensity features perform better compared to other two sets of features. Finally, after selecting the best features, multilayered perceptron network trained using Levenberg–Marquardt algorithm achieved the best results to classify the conditions of electrical equipment.     

An infrared thermal image processing framework based on superpixel algorithm to detect cracks on metal surface

Infrared thermography has been used increasingly as an effective non-destructive technique to detect cracks on metal surface. Due to many factors, infrared thermal image has low definition compared to visible image. The contrasts between cracks and sound areas in different thermal image frames of a specimen vary greatly with the recorded time. An accurate detection can only be obtained by glancing over the whole thermal video, which is a laborious work. Moreover, experience of the operator has a great important influence on the accuracy of detection result. In this paper, an infrared thermal image processing framework based on superpixel algorithm is proposed to accomplish crack detection automatically. Two popular superpixel algorithms are compared and one of them is selected to generate superpixels in this application. Combined features of superpixels were selected from both the raw gray level image and the high-pass filtered image. Fuzzy c-means clustering is used to cluster superpixels in order to segment infrared thermal image. Experimental results show that the proposed framework can recognize cracks on metal surface through infrared thermal image automatically.     

Low-velocity impact damage characterization of carbon fiber reinforced polymer (CFRP) using infrared thermography

Carbon fiber reinforced polymer (CFRP) after low-velocity impact is detected using infrared thermography, and different damages in the impacted composites are analyzed in the thermal maps.The thermal conductivity under pulse stimulation, frictional heating and thermal conductivity under ultrasonic stimulation of CFRP containing low-velocity impact damage are simulated using numerical simulation method. Then, the specimens successively exposed to the low-velocity impact are respectively detected using the pulse infrared thermography and ultrasonic infrared thermography. Through the numerical simulation and experimental investigation, the results obtained show that the combination of the above two detection methods can greatly improve the capability for detecting and evaluating the impact damage in CFRP. Different damages correspond to different infrared thermal images. The delamination damage, matrix cracking and fiber breakage are characterized as the block-shape hot spot, line-shape hot spot, and “

” shape hot spot respectively.     

Defect detection and evaluation of ultrasonic infrared thermography for aerospace CFRP composites

The ultrasonic infrared thermography Non-destructive Testing is introduced for detecting the impact damage of a CFRP specimen for Unmanned Aerial Vehicles. The characteristics of thermal images with damage are particularly analyzed. A Local Binary Fitting (LBF) model based on a non-Gaussian kernel function is used to segment the defect edge. In view of the discontinuity of defect in thermal images due to multilayered structure of composite materials, defect merging algorithms are proposed including time domain and space domain methods by using a few thermal images, and the defect geometric distortion during camera imaging is also compensated. The defect in the composite material can be quantitatively analyzed after the defect reconstruction. The experimental result has shown that the proposed algorithm can effectively detect and evaluate the impact damage of thermal images and the accuracy of quantitative assessment is correspondingly increased.     

Frequency modulated infrared imaging for thermal characterization of nanomaterials

The paper presents frequency modulated thermal wave imaging (FMTWI) as a fast and efficient non-contact technique for in-plane thermal characterization of thin plate nanomaterials. A novel excitation signal in the form of an up-chirp is applied and the thermal response is monitored using an infrared (IR) thermography based temperature sensing system. The in-plane thermal diffusivity of any sample can be measured using the multiple phase information extracted from a single run of the experiment. This feature provides a time efficient approach for thermal measurements using infrared thermography techniques. The theoretical background and experimental details of the technique are discussed, with practical measurement of thermal diffusivity of an empty anodic alumina (AAO) template in direction perpendicular to the nanochannel axis, in support.     

Inspection on SiC coated carbon–carbon composite with subsurface defects using pulsed thermography

An investigation on SiC coated carbon–carbon (C/C) composite plates has been undertaken by pulsed thermography. The heat transfer model has been built and the finite element method (FEM) is applied to solve the thermal model. The simulation results show that defects with DA/DP smaller than one can hardly be detected by an infrared camera with the sensitivity of 0.02 °C. Certificated experiments were performed on the built pulsed thermography system. The thermal wave signals have been processed by subtracting background image method (SBIM), pulsed phase thermography (PPT), and temperature–time logarithm fitting method (TtLFM). The limit DA/DP of defects in SiC coated C/C composite plates with the thickness of 6 mm that can be detected by pulsed thermography with the presented signal analysis algorithms has been obtained.     

Nondestructive testing of objects of complex shape using infrared thermography: Determination of the spatiotemporal distribution of the irradiation heat flux

The existing inverse methods used to determine the heat flux density require that the forward problem and the problem domain (geometry) be known. In this paper, in order to determine the spatiotemporal heat flux density without knowing the real problem domain, we propose an approach based on temporal tracking of the thermal front. The proposed approach is particularly relevant when a three-dimensional formulation is adopted for nondestructive testing using infrared thermography. For such a formulation, heat flux density resulting from the external thermal stimulus is needed and must be determined to accurately characterize the defects and reconstruct the internal geometry of the inspected objects. The proposed approach uses only two inputs: the time-dependent temperature of the frontal surface recorded by an infrared camera and the 3D point cloud of the frontal surface collected by a 3D scanner. The method is evaluated numerically on an object of complex shape. We consider the case of pulsed thermal stimulus as well as the cases of unit step and modulated thermal stimuli. An experimental validation is performed on a cylindrical object submitted to a pulsed thermal stimulus and a modulated thermal stimulus. The results show the accuracy of the method which can easily be implemented as the initial step of the three-dimensional quantitative nondestructive testing of objects using infrared thermography.     

A study on detection of micro-cracks in the dissimilar metal weld through ultrasound infrared thermography

This study was conducted to investigate a possibility of detecting stress corrosion crack defects in a pipe welded with dissimilar metals (STS304 and SA106 Gr. b) through infrared ultrasound thermography and lock-in phase method. The ultrasound generator was set as 250 W in output and 19.8 kHz in frequency. With experiment results, this study could detect, cracks located inside the dissimilar metal weld pipe through lock-in infrared thermography and compare thermography images obtained from both the inside and the outside when the ultrasound vibration was applied to the outer part of the pipe. Besides, after cutting off the pipe in the axial direction, this study conducted PT inspection. As a result, it was found there existed more than a single crack in a certain range inside the pipe, which made hot spots appear in a wide range on the thermography image. Moreover, through ultrasound infrared thermography and lock-in phase method this study verified the possibility of detecting micro-sized shattered cracks through ultrasound thermography, which were not easy to detect with the existing techniques.     

Introducing infrared thermography in soil dynamics

The paper introduces infrared thermography as a non-contact and non-destructive technique that conveniently offers the possibility of evaluating the energy-dissipating ability of soil, generally difficult to be determined using traditional techniques. It allows records and observations in real time of heat patterns produced by the dissipation of energy caused by friction between grains. Such dissipative heat occurs when soil is subjected to vibratory loading exceeding the characteristic threshold, and it evidences the distortion mechanism. This energy dissipation mechanism influences the wave propagation, intergranular attenuation, and dispersion through particles contacts. The infrared thermographic technique, which couples mechanical and thermal energy, offers the potential of directly monitoring the stress state of particle rearrangement and predicting the macroscopic mechanical response of soils subjected to cyclic, dynamic or vibratory loading. In addition, infrared thermography evidences the fuse effect of soil, capable to mitigate significantly the earthquake loading on engineering structures.     

用于显示乳房局部病灶组织红外热图像的伪彩色方法

通过检测人体体表每点的红外热辐射能量,可以得到反映体表温度分布的红外热图像。当乳房内部出现恶性肿瘤时,由于局部病灶组织具有异常的血运状态,会引起乳房表面病灶区域的温度显著升高。医生通过对乳房红外热图像病灶区域进行视觉分析、判断,可以实现对乳腺癌的检测。为了便于医生更好地发现这些病灶区域,本论文通过引入视觉因素,改进了传统的伪彩色显示方法,使病灶区域具有更鲜明的显示效果。这一方法的效果在47例乳腺癌病人的乳房红外热图像上得到了证实。采用这一方法对红外热图像病灶区域进行视觉分析所得到的结果,可以和采用近红外光谱等方法得到的组织血运状态进行对照比较,从而获得更为确切的诊断信息。     

Detection of osmotic damages in GRP boat hulls

Infrared thermography as a tool of non-destructive testing is method enabling visualization and estimation of structural anomalies and differences in structure’s topography. In presented paper problem of osmotic damage in submerged glass reinforced polymer structures is addressed. The osmotic damage can be detected by a simple humidity gauging, but for proper evaluation and estimation testing methods are restricted and hardly applicable. In this paper it is demonstrated that infrared thermography, based on estimation of heat wave propagation, can be used. Three methods are addressed; Pulsed thermography, Fast Fourier Transform and Continuous Morlet Wavelet. An additional image processing based on gradient approach is applied on all addressed methods. It is shown that the Continuous Morlet Wavelet is the most appropriate method for detection of osmotic damage.     

红外热不对称分析用于面神经功能损伤的客观评估

健康人体的温度分布存在一种双侧对称性,当面神经功能受损时,将改变这种热分布的对称性。人体热量大多通过红外辐射的形式散发,因此利用红外热成像技术可以有效捕捉这种红外热辐射分布的改变。本文提出一种新的热不对称分析的方法——有效热面积比,即计算面部特定区域与对侧区域的温差乘以温度异常区面积与总面积之比。利用这种方法对面神经功能损伤的患者和健康人群作对照性试验,结果显示:此方法的特异性和敏感性平均为0.90和0.87,比常规方法提高了7%和26%,有效热面积比与面神经功能的损伤程度正相关,平均为0.664。因此,关于诊断和评估面神经功能,红外热成像是一种有力的工具,有效热面积比是一项高效的临床指标。     

Narrative review: Diabetic foot and infrared thermography

Diabetic foot is one of the major complications experienced by diabetic patients. An early identification and appropriate treatment of diabetic foot problems can prevent devastating consequences such as limb amputation. Several studies have demonstrated that temperature variations in the plantar region can be related to diabetic foot problems. Infrared thermography has been successfully used to detect complication related to diabetic foot, mainly because it is presented as a rapid, non-contact and non-invasive technique to visualize the temperature distribution of the feet. In this review, an overview of studies that relate foot temperature with diabetic foot problems through infrared thermography is presented. Through this research, it can be appreciated the potential of infrared thermography and the benefits that this technique present in this application. This paper also presents the different methods for thermogram analysis and the advantages and disadvantages of each one, being the asymmetric analysis the method most used so far.     

Motion tracking in infrared imaging for quantitative medical diagnostic applications

In medical applications, infrared (IR) thermography is used to detect and examine the thermal signature of skin abnormalities by quantitatively analyzing skin temperature in steady state conditions or its evolution over time, captured in an image sequence. However, during the image acquisition period, the involuntary movements of the patient are unavoidable, and such movements will undermine the accuracy of temperature measurement for any particular location on the skin. In this study, a tracking approach using a template-based algorithm is proposed, to follow the involuntary motion of the subject in the IR image sequence. The motion tacking will allow to associate a temperature evolution to each spatial location on the body while the body moves relative to the image frame. The affine transformation model is adopted to estimate the motion parameters of the template image. The Lucas–Kanade algorithm is applied to search for the optimized parameters of the affine transformation. A weighting mask is incorporated into the algorithm to ensure its tracking robustness. To evaluate the feasibility of the tracking approach, two sets of IR image sequences with random in-plane motion were tested in our experiments. A steady-state (no heating or cooling) IR image sequence in which the skin temperature is in equilibrium with the environment was considered first. The thermal recovery IR image sequence, acquired when the skin is recovering from 60-s cooling, was the second case analyzed. By proper selection of the template image along with template update, satisfactory tracking results were obtained for both IR image sequences. The achieved tracking accuracies are promising in terms of satisfying the demands imposed by clinical applications of IR thermography.     

太赫兹激励的红外热波检测技术

本文的目的在于探索一种新的适用于红外热波检测技术的热激励方式——太赫兹(THz)热激励. 文中介绍了THz波周期性热激励的热传导理论模型; 尝试利用返波振荡器(返波管backward wave oscillator, BWO)太赫兹源对一块碳纤维基底吸波涂层板进行周期性THz热激励, 红外热像仪连续观测和记录试件表面温场变化, Canny边缘算法处理热图像显示缺陷; 检测结果与闪光灯脉冲激励的结果进行比较, 讨论了太赫兹波激励红外热波检测技术可能的优势. 实现了THz技术与红外热波无损检测技术的结合.     

复合材料脱粘缺陷的红外热像无损检测

以固体火箭发动机中的玻璃纤维复合材料壳体/绝热层试件的脱粘缺陷为研究对象,利用脉冲闪光灯热激励方式对试件进行加热,用红外热像仪实时监测试件的表面温度场,由表面温度差异来判定试件内部缺陷,然后通过对热像图进行图像增强处理和分割以定量识别缺陷。将实验结果与超声C扫描检测结果进行的对比分析表明:红外热像无损检测方法能够快速直观地发现深度5 mm以内、直径10 mm以上的脱粘缺陷,而超声C扫描检测更适合于对特定缺陷进行准确定量检测。     

Cellular neural networks for welding arc thermograms segmentation

Machine vision systems are used in many areas for monitoring of technological processes. Among this processes welding takes important place, where often infrared cameras are used. Besides reliable hardware, successful application of vision systems requires suitable software based on proper algorithms. One of most important group of image processing algorithms is connected to image segmentation. Obtainment of exact boundary of an object that changes shape in time, such as the welding arc, represented on a thermogram is not a trivial task. In the paper a segmentation method using supervised approach based on a cellular neural networks is presented. Simulated annealing and genetic algorithm were used for training of the network (template optimization). Comparison of proposed method to a well elaborated segmentation method based on region growing approach was made. Obtained results prove that the cellular neural network can be a valuable tool for infrared welding pool images segmentation.     

Fault detection of antenna arrays using infrared thermography

A fast and easy method for fault detection in antenna arrays using infrared thermography is presented. A thin, minimally perturbing, microwave absorption screen made of carbon loaded polymer is kept close in front of the faulty array. Electromagnetic waves falling on the screen increase its temperature. This temperature profile on the screen is identical to electric field intensity profile at the screen location. There is no temperature rise observed on the screen corresponding to non-radiating (faulty) elements and hence can be easily detected by IR thermography. The array input power is modulated at a low frequency which permits thermography to detect even weak fields. It also improves the resolution of thermal images. The power fed to the array is only 30 dBm. In order to show the utility of this technique, an example of 14 GHz 4 × 4 patch antenna array is given. The simulations are carried in CST Microwave Studio 2013. A good agreement between simulation and experimental results is observed.     

Vibration characteristics measurement of beam-like structures using infrared thermography

Infrared thermography (IRT) has matured and is now widely accepted as a condition monitoring tool where temperature is measured in a non-contact way. Since the late 1970s, it has been extensively used in vibrothermography (Sonic IR) non-destructive technique for the evaluation of surface cracks through the observation of thermal imaging of the vibration-induced crack heat generation. However, it has not received research attention on prediction of structural vibration behaviour, hence; the concept to date is not understood. Therefore, this paper explores its ability to fill the existing knowledge gap. To achieve this, two cantilever beam-like structures couple with a friction rod subjected to a forced excitations while infrared cameras capturing the thermal images on the friction interfaces. The analysed frictional temperature evolution using the Matlab Fast Fourier Transform (FFT) algorithm and the use of the heat conduction equation in conjunction with a finite difference approach successfully identifies the structural vibration characteristics; with maximum error of 0.28% and 20.71% for frequencies and displacements, respectively. These findings are particularly useful in overcoming many limitations inherent in some of the current vibration measuring techniques applied in structural integrity management such as strain gauge failures due to fatigue.     

Lock-in thermographic inspection of squats on rail steel head

The development of squat defects has become a major concern in numerous railway systems throughout the world. Infrared thermography is a relatively new non-destructive inspection technique used for a wide range of applications. However, it has not been used for rail squat detection. Lock-in thermography is a non-destructive inspection technique that utilizes an infrared camera to detect the thermal waves. A thermal image is produced, which displays the local thermal wave variation in phase or amplitude. In inhomogeneous materials, the amplitude and phase of the thermal wave carries information related to both the local thermal properties and the nature of the structure being inspected. By examining the infrared thermal signature of squat damage on the head of steel rails, it was possible to generate a relationship matching squat depth to thermal image phase angle, using appropriate experimental/numerical calibration. The results showed that with the additional data sets obtained from further experimental tests, the clarity of this relationship will be greatly improved to a level whereby infrared thermal contours can be directly translated into the precise subsurface behaviour of a squat.