Thermal Inspection Research Articles

Thermal Inspection of Subsurface Defects in Wind Turbine Blade Segments Under the Natural Solar Condition

Thermal Inspection of Subsurface Defects in Wind Turbine Blade Segments Under the Natural Solar Condition

The Importance of the Use of Unmanned Aerial Vehicles (UAVs) in the Oil and Gas Industry

The oil and gas industry, renowned for its extensive and intricate operations, confronts numerous challenges in maintaining and inspecting its infrastructure. Traditional inspection methodologies, often reliant on manual labor, are not only time-consuming and costly but also expose workers to hazardous conditions. These conventional methods necessitate the shutdown of operations, leading to considerable productivity losses and elevated costs. Over the past decade, the advent of unmanned aerial vehicles (UAVs) has introduced a transformative technology in this sector, providing a safer, more efficient, and cost-effective alternative to traditional inspection techniques. UAVs, equipped with advanced sensors and high-resolution cameras, facilitate detailed visual and thermal inspections of critical assets such as pipelines, flare stacks, and offshore platforms. These capabilities enable companies to perform routine inspections without halting operations, thereby minimizing downtime and operational disruptions. The implementation of UAV technology has notably enhanced safety by reducing the need for human intervention in perilous environments. For instance, the traditional inspection of flare stacks necessitates workers to ascend these structures, posing significant risks. UAVs obviate this requirement by delivering real-time visual data from secure distances. Moreover, the precision and accuracy inherent in UAV inspections contribute to the early detection of defects and potential issues, allowing for prompt maintenance and repairs, which further augment safety and operational efficiency. The environmental benefits of UAV technology are also noteworthy. By diminishing the reliance on heavy machinery and extensive transportation typically associated with inspections and maintenance, UAVs aid in reducing carbon emissions, thus aligning with the industry's sustainability objectives. In summary, the integration of UAVs into the oil and gas industry's inspection protocols represents a significant technological advancement. This integration aligns with the sector's goals of enhancing safety, efficiency, and environmental sustainability, marking a pivotal step forward in the industry's evolution.

Thermal inspection of hybrid nanofluid flows over a stretched cylinder at an oblique stagnation point with variable characteristics

AbstractThe enhanced thermal characteristics of hybrid nanofluids make them more versatile compared to conventional fluids. These improved thermal properties render hybrid nanomaterials highly practical for a wide range of applications, including solar systems, energy production, and cooling processes. In line with this perspective, the current study concentrates on evaluating the thermal performance of two unique hybrid nanofluid flows that impinge obliquely on a stretched cylinder. Two base fluids, FC‐77 and a binary mixture of water and ethylene glycol (50:50)%, have been considered, with the addition of nanoparticles such as single‐walled carbon nanotubes (SWCNTs) and multiwalled carbon nanotubes (MWCNTs). The said model's novelty is enhanced by the temperature dependent viscosity and thermal conductivity. Appropriate transformations are applied to derive a system of ordinary differential equations (ODEs), which are then solved numerically using the bvp4c method. A thorough examination is conducted on the physical phenomenon of pertinent parameters, accompanied by graphical representations. The results revealed that, for the FC‐77 coolant‐based hybrid nanofluid, mounting the particle volume fraction leads to a significant reduction in temperature distribution. Additionally, it is perceived that the presence of a variable viscosity parameter causes a reduction in the surface drag coefficient as well as the axial and tangential velocities. The validity of the proposed flow model is demonstrated by comparing the results with those from an earlier study.

Automated mission planning for aerial large‐scale power plant thermal inspection

AbstractClose‐range aerial inspection of large‐scale industrial facilities such as power plants is complex. It is characterized by a few areas suitable for safe landing, many obstacles, complicated radio communication, and so forth. The paper presented a new offline approach for automated mission planning in such conditions. It is based on novel concepts of ‐shaped flight profile and safe altitude map. These concepts reduce the mission planning task to a multiple traveling salesmen problem on a two‐dimensional map, which is solved using rapidly exploring random tree and genetic algorithms. A computational fluid dynamics‐based local turbulence map concept was proposed to avoid turbulence zones during inspection flights. As an advantage, this map can be generated at least 6.8× faster than the known approaches. Our new multicopter flight time prediction model provides an error of less than 10% in most cases and significantly outperforms those implemented in commercial mission planning software. All the proposed solutions were verified during a 2400‐MW power plant inspection. Our algorithms managed to plan to visit all the inspection points in six routes, approximately 15 min long each. This mission set has a comparable overall duration but better safety and even battery usage compared with the routes planned by a qualified operator. Moreover, the designed aerial inspection system provides higher quality images than manually from the ground using a thermal camera with two times higher sensitivity and equipped with more advanced optics. To our knowledge, this research is the first to report the successful implementation of autonomous unmanned aerial vehicle‐based power equipment diagnostics on a large‐scale thermal power plant.

EFEKTIFAS PEMINDAI TERMAL UNTUK MENDETEKSI COVID-19

Infrared thermal inspection through the use of thermal scanners, has been widely implemented throughout the world. This research aims to analyze the effectiveness of thermal scanners in detecting Covid-19. The research was conducted using a cross-sectional research design with a retrospective approach. This research was conducted in the period January-June 2021. The sample in this study was taken from the total population. Where the number of research subjects is all samples that have met the inclusion and exclusion criteria. The research results show that a high positive likelihood ratio of 15 means that individuals who are confirmed positive for COVID-19 are 15 times more likely to experience fever (temperature above 37.5˚C) than healthy individuals. This implies that a positive thermal scanner is a significant indicator of a confirmed positive SARS CoV-2 test result. Thermal scanners have good sensitivity and specificity in detecting body temperature. Even though there is a decrease in the sensitivity of thermal scanners in a pandemic situation, this research shows that the use of thermal scanners is a crucial effort in detecting body temperature when the virus is transmitted to the majority of the population.

Non-destructive Thermal Monitoring of Temperature and Flow Rate of the Heat Carrier in a Heating Device

Conducting various calculations for the heating system of a building under operational conditions is impossible without knowledge of the temperature and flow rate of the heat carrier at specific points. Contact measurement means are not always applicable, especially for small-diameter pipelines. Measurement techniques based on the theory of non-destructive thermal inspection allow for remote and timely acquisition of all necessary information. The object of the study is the floor node of the building's heating system. The subject of the study is the temperature and flow rate of the heat carrier passing through the heating device. The research aim is to determine the temperature and flow rate of the heat carrier passing through the heating device under operational conditions. The research method involves the theory of non-destructive thermal inspection, as well as heat balance and heat transfer equations for a vertical flat wall. Research findings reveal that during thermovisual inspection, the temperature of the heat carrier in the supply and return pipelines of the floor node respectively amounted to 51.6 ℃ and 49.6 ℃. The flow rate of the heat carrier through the heating device model MS-140M2-500, with a heat transfer coefficient of 8.5 W/(m²⋅K), was determined to be 195.0 kg/h. Recommendations include utilizing a thermal imager with an absolute measurement error not exceeding ±0.15 ℃ for determining the flow rate of the heat carrier through the heating device. The influence of measurement error of indoor air temperature on the accuracy of determining the heat carrier flow rate is insignificant (not exceeding ±2%). The relative error in determining the heat transfer coefficient of the heating device does not exceed ±1%.

Application of the Conjugate Gradient Method for Predicting Unknown Heat Flux in 2D Plat under Effect of Insulation

When an anomaly is discovered during a thermal inspection of industrial equipment, the diagnosis of finding the heat source is made more difficult by the presence of heat insulation. The use of the Conjugate Gradient Method (CGM) to solve the unknown heat flux in Inverse Heat Conduction Problem (IHCP) under insulation condition has been discussed. This method is used to predict a heat flux by utilizing temperature data at any points of measurement. The study deals with the structure of 2D thin plate at steady state. A copper plate with a thickness of 1 mm is used as specimen. White glass wool is used to thermally insulate the plate on the back surface. An electrical heater is plate mounted and operated by varying the DC voltage. A datalogger with thermocouple sensors records plate temperature changes. Software for solving the IHCP based on the CGM was developed. Initially, the software was implemented using synthetic data obtained from the forward heat conduction equations with a known heat flux. Simulated measurement data are assumed to have high accuracy (± 0.1 ºC). Determination of heat flux with the CGM gives very satisfactory results with a low error below 0.12%. The CGM was then applied using experimental data. With a measurement error of ± 0.5 ºC, the computational stopping criterion can still be met satisfactorily. In real installations, equipment is sometimes partially or completely isolated. In the experiment, this phenomenon is simulated by varying the isolation area as follows: 0%, 25%, 50% and 100%. The results of the flux calculation are correlated with the real flux supplied by the electrical heater. Each type of insulation area has a similar curve. By obtaining the correlation equation, the equivalent heat flux from calculation to real and vice versa can be carried out.

Thermal Mapping from Point Clouds to 3D Building Model Facades

Thermal inspection of buildings regarding efficient energy use is an increasing need in today’s energy-demanding world. This paper proposes a framework for mapping temperature attributes from thermal point clouds onto building facades. The goal is to generate thermal textures for three-dimensional (3D) analysis. Classical texture generation methods project facade images directly onto a 3D building model. Due to the limited level of detail of these models, projection errors occur. Therefore, we use point clouds from mobile laser scanning extended by intensities extracted from thermal infrared (TIR) image sequences. We are not using 3D reconstructed point clouds because of the limited geometric density and accuracy of TIR images, which can lead to poor 3D reconstruction. We project these thermal point clouds onto facades using a mapping algorithm. The algorithm uses a nearest neighbor search to find an optimal nearest point with three different approaches: “Minimize angle to normal”, “Minimize perpendicular distance to normal”, and “Minimize only distance”. Instead of interpolation, nearest neighbor is used because it retains the original temperature values. The thermal intensities of the optimal nearest points are weighted by resolution layers and mapped to the facade. The approach “Minimize perpendicular distance to normal” yields the finest texture resolution at a reasonable processing time. The accuracy of the generated texture is evaluated based on estimating the shift of the window corner points from a ground truth texture. A performance metric root-mean-square deviation (RMSD) value that measures this shift is calculated. In terms of accuracy, the nearest neighbor method outperformed bilinear interpolation and an existing TIR image-based texturing method.

Thermal inspection of photovoltaic modules with deep convolutional neural networks on edge devices in AUV

Solar photovoltaic (PV), a green energy harvesting system, is growing worldwide rapidly. It is a friendly environmental energy system. During operation, anomalies could appear in the PV modules, which reduce energy harvesting efficiency, shorten the lifetime and lead to an increase in the amount of heavy metals being released into the environment. In this research, a remote sensing method is proposed for the fast and efficient detection of anomalies in photovoltaic (PV) systems. An infrared radiation (IR) camera mounted on flying vehicles (e.g., drone) to capture IR images of solar panels. Then, convolutional neural networks (CNN) are developed to detect abnormal cells in the PV systems. The CNN model are then quantized and implemented on edge devices for real-time detection of anomalies. We evaluated these models on 11 types of anomalies in PV modules collected from 826 solar panels worldwide. Moreover, the classification decision of each layer of the CNN model can be visualized by the Gradient-weighted Class Activation Mapping method to reinforce the classification output. In addition, we implemented the models on an edge device (Jetson Nano) to evaluate real-time inspection capabilities. The proposed model is efficient compared to the other previous models, which takes only 1.04 ms to progress one image on average while still yields a high accuracy of 85.35% when running on the Jetson Nano board.

The Influence of Wind Speed on the Thermal Imaging Clarity Based Inspection for Transmission Line Conductors

Infrared thermal inspection is the primary way to detect transmission line conductor faults. Nevertheless, the conventional inspections are carried out at low wind speeds, causing high investment and low efficiency. Besides, the relationship between wind speed and infrared image clarity of transmission lines has yet to be investigated. In this paper, a temperature difference-based definition of infrared imaging contrast that quantifies image clarity is firstly proposed. To explore the relationship between thermal imaging contrast and wind speed, thermal cycling tests are carried out. Based on tests and membership frequency research, a method for predicting whether a clear image could be obtained is derived. In addition, the accuracy of the proposed method is verified in a natural environment. The results show that wind speed is the only variable that affects infrared imaging contrast. High clarity image can be acquired when the contrast ranges from 0.35 to 0.78. Moreover, the average error between the practical and calculated values of contrast in the natural test is 9.1%, indicating that the proposed method is effective. The conclusion in this work provides feasible guiding significance for the infrared thermal imaging inspection engineering of overhead transmission lines.

Obstacle and Collision Avoiding Drone

Abstract: Larger drones, such as those used for commercial operations, are much less likely to have obstacle avoidance features because they fly higher in the sky, where it is less likely that they will encounter static obstacles and more likely that they will encounter dynamic obstacles while also flying faster; the market’s offerings for static obstacle avoidance do not meet those needs. Since smaller drones are typically used for hobbyists and smaller-scale operations like thermal inspection, hazard detection inside of warehouses, and up-close inspection of wind turbines and power lines, obstacle avoidance is typically limited to these types of smaller drones. The performance requirements for Detect-and-Avoid capabilities for dynamic objects vary since infrastructure masking can occasionally reduce risks. For instance, you have an additional layer of protection when flying near structures or in a deep valley because manned aviation is less likely to be using the same airspace. Similar to this, infrastructure shadowing involves flying 50 feet or less away from a power line that is exactly 50 feet above the structure being “shadowed.” Given that you are more unlikely to come across any manned aircraft, this mitigation level is higher than just masking.

Thermal inspection for viscous dissipation slip flow of hybrid nanofluid (TiO2–Al2O3/C2H6O2) using cylinder, platelet and blade shape features

Hybrid nanofluid are the modified class of nanofluids with extra high thermal performances and present different applications in automotive cooling, heat transfer devices, solar collectors, engine applications, fusion processes, machine cutting, chemical processes etc. This thermal research explores the heat transfer assessment due to hybrid nanofluid with of different shape features. The thermal inspections regarding the hybrid nanofluid model are justified with aluminium oxide and titanium nanoparticles. The base liquid properties are disclosed with ethylene glycol material. The novel impact of current model is the presentation of different shape features namely Platelets, blade and cylinder. Different thermal properties of utilized nanoparticles at various flow constraints are reported. The problem of hybrid nanofluid model is modified in view of slip mechanism, magnetic force and viscous dissipation. The heat transfer observations for decomposition of TiO2–Al2O3/C2H6O2 is assessed by using the convective boundary conditions. The shooting methodology is involved for finding the numerical observations of problem. Graphical impact of thermal parameters is observed for TiO2–Al2O3/C2H6O2 hybrid decomposition. The pronounced observations reveal that thermal rate enhanced for blade shaped titanium oxide-ethylene glycol decomposition. The wall shear force reduces for blade shaped titanium oxide nanoparticles.

DIRECTIONS OF USE OF UNMANNED AERIAL VEHICLES AT THE AIRPORTS

The article is devoted to the available directions for the use of unmanned aerial vehicles at the airports. The task of this scientific research was to single out promising directions for the unmanned aerial vehicles use at the airports by analyzing and summarizing information from various sources, expertly justifying the identified directions. The selection of such directions has been carried out by analyzing and summarizing information from various sources. Nowadays there is a fast development of the service provision by unmanned aerial vehicles in different fields of practical activity: security monitoring; transportation of small-sized cargo; visual, spectral and thermal inspection of structures; monitoring of linear network infrastructure; photography and mapping; introduction of agricultural fertilizers and chemicals; atmospheric research. The method of expert evaluations has been used, expert judgments have been checked for consistency. Experts evaluated the proposed directions from the point of view of the importance and expediency of using unmanned aerial vehicles in different directions. The identified directions have been expertly substantiated and a system of priorities for the use of unmanned aerial vehicles at the airports has been built.

Thermal performance of iron oxide and copper (Fe3O4, Cu) in hybrid nanofluid flow of Casson material with Hall current via complex wavy channel

The nanoparticles have substantial uses in the treatment of several diseases and in drug delivery systems and the nanoparticles are injected in the base fluid which is transported in the cardiovascular system on the mechanism of peristalsis. This study highlights the Casson hybrid nanofluid thermal inspection with blood base fluid. The copper and iron oxide nanoparticles are used to assess the hybrid nanofluid characteristics. The conduit for the present analysis is considered non-uniform complex wavy and curved. The base fluid is considered as a Casson fluid which reports the shear thinning and thickening consequences of blood base liquid. The fundamental conservation laws are utilized to model the flow problem and simplified under the assumption of long wavelength and creeping transport. The shooting method is used to compute the different flow and heat transfer characteristics The impact of various interesting parameters is examined graphically.

Implementation of Non-Contact Temperature Distribution Monitoring Solutions for Railway Vehicles in a Sustainability Development System Transport.

The implementation of temperature sensors represented by thermal imaging cameras is becoming increasingly rational. It is playing an important role in the socio-economic environment, in industry, scientific-research work. The main objective of the work is to assess the quality of the railway vehicles in exploitation and their thermal insulation, localise thermal bridges, and the tightness of the body using the FLIR-E6390 thermal inspection camera. An integration of test methods (research methods) was used including a diagnostic method based on a thermographic study integrated with the system approach method and system failure mode effects analysis (SFMEA). The scientific-research work included studies of seven types of railway vehicles in exploitation. A number of conclusions were reached. Specifically providing implementation of innovative and non-contact temperature distribution monitoring solutions for railway vehicles in a sustainability development system transport. Demonstrated the disparities between the different types of vehicles. Next, the identification of critical elements of their thermal insulation, the location of thermal bridges, and the tightness of the body of the rail vehicles, particularly the doors and inter-unit connections. The study covered the state of consumption of stationary electricity (for non-traction needs), implementing innovative indicators for stationary electricity consumption of railway vehicles as a new approach.

A comparative thermal investigation for modified hybrid nanofluid model (Al2O3–SiO2–TiO2)/(C2H6O2) due to curved radiated surface

The nanofluids containing more two different types of nanoparticles with suspension of base fluids is referred to hybrid nanofluids. The modified class of hybrid type nanomaterials is new impressive category of nanofluid model which obtained with suspension of base fluid into more than two different types of nanoparticles. The heating influence and capacitance of modified hybrid nanoparticles is more impressive as compared to hybrid model and traditional nanofluid model. Following such motivations in mind, current exploration reports the comparative thermal inspection of three types of nanoparticles like aluminium oxide ( A l 2 O 3 ) , silicon dioxide ( S i O 2 ) and titanium dioxide ( T i O 2 ) with suspension of base particles along with ethylene glycol ( C 2 H 6 O 2 ) base fluid. The flow pattern for such nanoparticles flow is observed due to curved surface comprising the stagnation point flow. The Casson fluid model is used to identify the rheological impact and base fluid characterization. The nonlinear radiation impact is also utilized to modify the model. The Keller box numerical outcomes against the developed set of equations are obtained. A comparative investigation for the suspension of modified hybrid nanomaterial ( A l 2 O 3 + S i O 2 + T i O 2 − C 2 H 6 O 2 ) is inspected.

Hand-held and UAV camera comparison in building thermal inspection process

Thermal building inspections indicate the growing interest among researchers due to the global climate changes resulting in legislations and policy contribution to low-energy consumption. The technologies applied during the experiments involve infrared cameras: both hand-held and on unmanned aerial vehicles. The research conducted in the public building in Kielce included the analysis of glass partition from the inside of the building by means of hand-held and UAV camera. The temperature distributions presented in the graphs proved that both methods are accurate in case of such investigations. However, during the experiments, it was concluded that hand-held camera is far more convenient.

Real-time pixel-level fusion of colour and thermal (RGB-T) imagery via extrinsic optical alignment: Scope for automating building inspections

Building inspections and energy surveys are performed to detect and diagnose building defects, however, existing inspection methods are highly labour intensive, time consuming, and not suitable for large-scale audits. This work presents a thermal-colour fusion technique using pre-capture optical alignment that eliminates the need for compute-intensive post-processing of data. The coinciding axes of dual cameras also prevent parallax errors, which helps expand its applications to near proximity or indoor thermal inspection as well. A prototype of this design was assembled and tested, which showed a pixel-level accurate alignment of thermal and colour camera imagery with minimal computation. The research and development in this paper provides scope and feasibility to automate building inspection techniques through drone-based low-powered embedded machine learning models and identify faults in real-time for large-scale surveys of building façades.

Towards the Automation of Infrared Thermography Inspections for Industrial Maintenance Applications

The maintenance of industrial equipment extends its useful life, improves its efficiency, reduces the number of failures, and increases the safety of its use. This study proposes a methodology to develop a predictive maintenance tool based on infrared thermographic measures capable of anticipating failures in industrial equipment. The thermal response of selected equipment in normal operation and in controlled induced anomalous operation was analyzed. The characterization of these situations enabled the development of a machine learning system capable of predicting malfunctions. Different options within the available conventional machine learning techniques were analyzed, assessed, and finally selected for electronic equipment maintenance activities. This study provides advances towards the robust application of machine learning combined with infrared thermography and augmented reality for maintenance applications of industrial equipment. The predictive maintenance system finally selected enables automatic quick hand-held thermal inspections using 3D object detection and a pose estimation algorithm, making predictions with an accuracy of 94% at an inference time of 0.006 s.

Heat and power plant chimneys thermal inspection with an infrared camera

Thermography is getting more and more popular in many fields of everyday life nowadays. It is successfully applied in heat investigations. Infrared cameras imaging includes thermal analyses of building physics, thermal bridges or insulation improvement inspection. Flir E30 infrared camera was used in order to conduct measurements of two chimneys located in Kielce Power Station in Poland. The first tested facility is a structural steel chimney thermally isolated with mineral wool. The other chimney is built of reinforced concrete material. An infrared camera tests enabled the creation of the diagrams presenting the temperature distribution along the chimneys in different orientations. The research proved the correct functioning of both chimneys.