Use Of Thermal Sensors Research Articles

Core loss determination in electric machines using short‐time transient thermal measurements

AbstractThis paper introduces a novel application of the inverse modelling method, which is designed to estimate core losses in both the stator and rotor regions of an electrical machine. The technique focuses on the use of short‐term transient temperature measurements obtained from the stator core of a slotless induction machine, with a focus on validating the measured temperature rise through a forward model. The measurement setup involves two primary approaches: (i) the use of thermal sensors embedded in a printed circuit board inside the stator core and (ii) surface sensors embedded on the stator yoke. Through the use of this innovative approach, the results indicate that the inverse modelling technique is highly effective in predicting core losses based on short‐time transient temperature rise measurements.

Using YOLO Object Detection to Identify Hare and Roe Deer in Thermal Aerial Video Footage—Possible Future Applications in Real-Time Automatic Drone Surveillance and Wildlife Monitoring

Wildlife monitoring can be time-consuming and expensive, but the fast-developing technologies of uncrewed aerial vehicles, sensors, and machine learning pave the way for automated monitoring. In this study, we trained YOLOv5 neural networks to detect points of interest, hare (Lepus europaeus), and roe deer (Capreolus capreolus) in thermal aerial footage and proposed a method to manually assess the parameter mean average precision (mAP) compared to the number of actual false positive and false negative detections in a subsample. This showed that a mAP close to 1 for a trained model does not necessarily mean perfect detection and provided a method to gain insights into the parameters affecting the trained models’ precision. Furthermore, we provided a basic, conceptual algorithm for implementing real-time object detection in uncrewed aircraft systems equipped with thermal sensors, high zoom capabilities, and a laser rangefinder. Real-time object detection is becoming an invaluable complementary tool for the monitoring of cryptic and nocturnal animals with the use of thermal sensors.

CNN Based Rat Detection using Thermal Sensor

The detection and control of rats in commercial buildings and industries are crucial issues due to the damage they can cause to Godowns and equipment. Traditional methods of rat detection and control can be time-consuming and expensive and may not always be effective. This has brought the exploration of machine learning-based approaches, which can provide more accurate and efficient detection of rats. One such approach is the use of thermal sensors in conjunction with machine learning algorithms to detect rats in commercial buildings, industries, etc. Thermal sensors can detect the body heat of rats, and machine learning algorithms can be trained to analyze thermal data and accurately identify the presence of rats. This approach has several advantages over traditional methods, including higher accuracy, long-range and faster detection. The machine learning algorithms used in this approach can be trained using large datasets of thermal images of rats, which can be obtained using thermal cameras

Evidence on the efficacy of small unoccupied aircraft systems (UAS) as a survey tool for North American terrestrial, vertebrate animals: a systematic map

BackgroundSmall unoccupied aircraft systems (UAS) are replacing or supplementing occupied aircraft and ground-based surveys in animal monitoring due to improved sensors, efficiency, costs, and logistical benefits. Numerous UAS and sensors are available and have been used in various methods. However, justification for selection or methods used are not typically offered in published literature. Furthermore, existing reviews do not adequately cover past and current UAS applications for animal monitoring, nor their associated UAS/sensor characteristics and environmental considerations. We present a systematic map that collects and consolidates evidence pertaining to UAS monitoring of animals.MethodsWe investigated the current state of knowledge on UAS applications in terrestrial animal monitoring by using an accurate, comprehensive, and repeatable systematic map approach. We searched relevant peer-reviewed and grey literature, as well as dissertations and theses, using online publication databases, Google Scholar, and by request through a professional network of collaborators and publicly available websites. We used a tiered approach to article exclusion with eligible studies being those that monitor (i.e., identify, count, estimate, etc.) terrestrial vertebrate animals. Extracted metadata concerning UAS, sensors, animals, methodology, and results were recorded in Microsoft Access. We queried and catalogued evidence in the final database to produce tables, figures, and geographic maps to accompany this full narrative review, answering our primary and secondary questions.Review findingsWe found 5539 articles from our literature searches of which 216 were included with extracted metadata categories in our database and narrative review. Studies exhibited exponential growth over time but have levelled off between 2019 and 2021 and were primarily conducted in North America, Australia, and Antarctica. Each metadata category had major clusters and gaps, which are described in the narrative review.ConclusionsOur systematic map provides a useful synthesis of current applications of UAS-animal related studies and identifies major knowledge clusters (well-represented subtopics that are amenable to full synthesis by a systematic review) and gaps (unreported or underrepresented topics that warrant additional primary research) that guide future research directions and UAS applications. The literature for the use of UAS to conduct animal surveys has expanded intensely since its inception in 2006 but is still in its infancy. Since 2015, technological improvements and subsequent cost reductions facilitated widespread research, often to validate UAS technology to survey single species with application of descriptive statistics over limited spatial and temporal scales. Studies since the 2015 expansion have still generally focused on large birds or mammals in open landscapes of 4 countries, but regulations, such as maximum altitude and line-of-sight limitations, remain barriers to improved animal surveys with UAS. Critical knowledge gaps include the lack of (1) best practices for using UAS to conduct standardized surveys in general, (2) best practices to survey whole wildlife communities in delineated areas, and (3) data on factors affecting bias in counting animals from UAS images. Promising advances include the use of thermal sensors in forested environments or nocturnal surveys and the development of automated or semi-automated machine-learning algorithms to accurately detect, identify, and count animals from UAS images.

Thermal Attack In Linux System

Many operating systems now a days make use of thermal sensors for monitoring the CPU temperature. The monitoring of CPU temperature mainly includes measuring the frequency, energy consumption temperature of the CPU. Some unprivileged users can make use of this thermal sensor to gain access to some secret information. The unprivileged users used to execute programs in order to generate heat within the CPU in order to generate the covert channel in which leakage of information may take place

Usage of IR Sensors in the HVAC Systems, Vehicle and Manufacturing Industries: A Review

The use of thermal sensors is increasing in response to dealing with the problems of the visible light spectrum. These sensors measure the temperature of the object and convert it to some readable output. There is a diverse range of temperature sensors, and different sensors are used for different purposes. The choice of the sensor depends on the cost of the sensor, resolution, and level of accuracy. For instance, an IR camera combined with the RGB sensor can produce better human activity recognition. However, increase the cost of the machine. For some applications, a high resolution is not required and a low-cost sensor can satisfy the need. In this survey, we discuss the employment of thermal sensors in HVAC systems, vehicle, and manufacturing industries as they are heavily used in these industries. We reported the types of available thermal sensors and the sensors commonly used in each industry. This is followed by a comprehensive review of the application-specific methods. In the end, we may say that the selection of the thermal sensor has much importance as well as the choice of the suitable algorithms according to the given conditions to avail the maximum accuracy in our results.

RESOLUTION ENHANCEMENT OF INFRARED THERMAL IMAGING BY PANSHARPENING ALGORITHMS

Abstract. One common tool in Cultural Heritage inspections is thermal cameras, which are sensitive to the infrared part of the electromagnetic spectrum. But the resolution of these sensors is quite lower than other kinds like visible spectrum range cameras. Typically, the sensors in thermal cameras do not exceed the megapixel frontier. This limitation becomes a problem when trying to combine the information from the thermal images with data from other sensors with much higher resolution such as visible RGB cameras in the same project.In Remote Sensing, algorithms have been designed to fuse multispectral images with panchromatic images (in origin from satellite platforms) to enhance the resolution of lower resolution images with higher resolution ones. These processes are known as pansharpening. Although pansharpening procedures are widely known, they have not been tested working with thermal imaging. The first approach of merging thermal and visual spectrum images to enhance the resolution of the original thermal image involved applying the intensity-hue-saturation (IHS) algorithm (Lagüela et al., 2012, Kuenzer and Dech, 2013). These works only studied one particular algorithm and they did not include any quality study of the results.Our work contains a complete review of a bigger pansharpening algorithms’ set and provides an in-depth study of thermal imaging pansharpening, with a numerical assessment. Our research allows the use of thermal sensors with a lower resolution than other types of sensors used simultaneously in the same project.

Investigation into the Lithium-Ion Battery Fire Resistance Testing Procedure for Commercial Use

Lithium-ion batteries (LIBs) have many advantages (e.g., high voltage and long-life cycle) in comparison to other energy storage technologies (e.g., lead acid), resulting in their applicability in a wide variety of structures. Simultaneously, the thermal stability of LIBs is relatively poor and can be damaged by exposure to fire. This paper presents an investigation into a fire resistance safety test for LIBs and the use of thermal sensors to evaluate exposure conditions and estimate the temperatures to which cells are subjected. Temperature distribution data and statistical analysis show significant differences of over 200 ∘C, indicating the stochastic nature of the heating curve despite following the testing procedure requirements. We concluded that the current testing procedure is inadequate for the reliable testing of LIBs, leaving an alarming loophole in the fire safety evaluation. The observed instability is mostly related to wind speed and direction, and fire source size.

Identifying optimal wavelengths to maximise the detection rates of marine fauna from aerial surveys

Aerial surveys are increasingly used for assessing the presence and abundance of many large faunal species. However, detection rates often suffer significant sightability errors. Using sensors that capture thermal infrared can sometimes improve the detectability of fauna by increasing the contrast of target animals against their surrounds. However, there are several situations where this does not work well. Submerged fauna in marine environments are one example, and where the detection error can be substantial. To identify what wavelength selection might enhance detectability rates beyond standard cameras, we used a drone-based hyperspectral sensor to measure the reflectance of 64 animals and their corresponding surrounds. Fauna included white sharks (Carcharodon carcharias), bottlenose dolphins (Tursiops aduncus), and various other species of ray (Rhinoptera neglecta, Aetobatus narinari, Rhynchobatus australiae) and fish (Seriola lalandi). Data were analysed using Generalized Additive Mixed-Models (GAMM) to compare the difference in spectral reflectance between fauna and their surrounds. The GAMMs showed little difference between submerged fauna groups, but indicated that a band of wavelengths between 514 and 554 nm provided the greatest contrast between fauna and their surrounding backgrounds. This was also consistent across the range of environmental conditions. We contend that restricting the spectral input to a standard high-resolution camera, or focusing on the channels that accentuate the green colours in post-processing, will likely result in increased accuracy in the detection of submerged fauna. This approach may also be applied to fauna surveys in other landscapes, particularly where the use of thermal sensors is not appropriate.

Thermal behavior analysis and thermal error compensation for motorized spindle of machine tools

The thermal error deformation of motorized spindle plays an important role in the precision machining, while error compensation has been proved to be a cost-effective way. Herein a symmetrical solution for the thermal error problem of spindle is proposed based on the thermal behavior analysis. Firstly, the heat generating and transfer mechanism are described considering the heat sources. Next, ANSYS is used to achieve the steady-state and the transient thermal field distribution as well as the related deformation with the given thermal load and boundary condition. Furthermore, the NEM is proposed to predict the thermal error under random rotating speed with no use of thermal sensors, followed by the determination of two important parameters. The verification experiment of the thermal error under random rotating speed is executed. The External Machine Zero Point Shift function of the CNC system is adopted to develop the real-time compensation system on the spindle of HDBS-63 machining center. The maximum axial thermal error is greatly reduced from 55 to 16 um, while the radial one similarly reduced from 15 to 6 um. Both are improved 73% and 63% respectively. The experiment results show that NEM method is simple but of good reliability and practicality.

Photothermal converters for quantitative 2D and 3D real-time TeraHertz imaging

Recent advances for the measurement of TeraHertz (THz) radiation by using original IR temperature flux sensors are presented. The bolometer principle is used for designing simple thermal converters for THz radiations (measurement of the temperature increase of a sensitive absorber). Most of these sensors are efficient, sensitive and fast enough for quantitative measurement of THz source power as well as for 2D and 3D THz imaging. By combining optical and thermal technologies, we extend and adapt the use of thermal sensors to large THz wavelength till 3 mm (0.1 THz). A large variety of mono- or arrayed- thermal sensors is used and optimized for real-time room temperature THz imaging using adapted IR focal-plane microbolometers array (FPMA) camera. Optimisation and adaptation of such FPMA is discussed and a new arrayed prototype device of THz-Thermal Converter, “TTC”, for full-field real-time THz imaging is presented. This small size, low cost and efficient prototype design is discussed from the thermal point of view and is characterized using a compact powerful THz source. Their sensitivity is evaluated and the obtained 2D and 3D images clearly illustrates the high potential of this new kind of THz camera. Finally, it is shown that non-arrayed extended plane TTCs (EMIR sensitive screens) coupled to FPA cameras produce THz images free of diffraction phenomena.

Thermal anemometry, current state, and future directions

The variation in heat transfer between a fine wire and the surrounding fluid has traditionally been the most accepted method for measuring the detailed movements of a flow fluid. This paper reviews the present understanding of thermal techniques as used in research and recent advancements of the technique. While the basic research sensor is still a fine wire, modern electronics has greatly simplified data analysis as well as established constant temperature operation of the sensor as the control method of choice. Film sensors have extended the use of thermal sensors to new applications. Comparisons with laser Doppler velocimeters help to identify experiments where thermal sensors still represent the best choice. The ability of modern electronics to easily address the typical nonlinear response of thermal sensors has resulted in increased use for commercial applications. While in these applications fast response can be a factor (e.g., fuel flow control in engines), generally only average flows are needed. As a result, calibration shifts due to deposits on the sensor surface when exposed to contaminated fluids can generally be reduced to acceptable levels by using larger sensors.