Browse Topic: Imaging and visualization

Items (6,430)
The mobility industry is rapidly advancing towards more autonomous modes of transportation with the adoption of sophisticated self-driving technologies. However, a critical challenge, being the lack of standardized norms for defining, measuring, and ensuring vehicle visibility across various dynamic traffic environments, remains. This lack of awareness of visibility is hindering the development of new regulations for vehicle visibility and the controlled transition to a fully-integrated autonomous future. While current efforts focus on improving sensing technologies like computer vision, LiDAR systems, and sensor fusion development, two key issues remain unresolved: 1 The absence of a representative and realistic three-dimensional color visibility model for measuring and comparing the visibility of complex shapes with large but varying color coated three-dimensional surface areas. 2 The need for enhanced visibility solutions that improve visibility and vehicle detectability for all
Mijnen, Paul W.Moerenburg, Joost H.
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
Pohl, EricScheibe, SebastianMünster, MarcoOsebek, ManuelKopp, GerhardSiefkes, Tjark
In order to comply with increasingly stringent emission regulations and ensure clean air, wall-flow particulate filters are predominantly used in exhaust gas aftertreatment systems of combustion engines to remove reactive soot and inert ash particles from exhaust gases. These filters consist of parallel porous channels with alternately closed ends, effectively separating particles by forming a layer on the filter surface. However, the accumulated particulate layer increases the pressure drop across the filter, requiring periodic filter regeneration. During regeneration, soot oxidation breaks up the particulate layer, while resuspension and transport of individual agglomerates can occur. These phenomena are influenced by gas temperature and velocity, as well as by the dispersity and reactivity of the soot particles. Renewable and biomass based fuels can produce different types of soot with different reactivities and dispersities. Therefore, this study focuses on the influences of soot
Desens, OleHagen, Fabian P.Meyer, JörgDittler, Achim
The video systems include a camera, display, and lights. Video is the recording, reproducing, or broadcasting of moving visual images as illustrated in Figure 1. A camera video imaging system is a system composed of a camera and a monitor, as well as other components, in which the monitor provides a real-time or near real-time visual image of the scene captured by the camera. Such systems are capable of providing remote views to the pilot and can therefore be used to provide improved visibility (for example, coverage of blind spots). In general, camera video systems may be used in the pilot’s work position for purposes of improving airplane and corresponding environmental visibility. Examples of aircraft video system applications include: Ground maneuver or taxi camera system Flight deck entry video surveillance system Cargo loading and unloading Cargo compartment livestock monitoring Monitoring systems that are used to track the external, internal, and security functions of an
A-20B Exterior Lighting Committee
The escalating complexity at intersections challenges the safety of the interaction between vehicles and pedestrians, especially for those with mobility impairments. Traditional traffic control systems detect pedestrians through costly technologies such as LiDAR and radar, limiting their adoption due to high costs and static programming. Therefore, the article proposes a customized signalized intersection control (CSIC) algorithm for pedestrian safety enhancement. This algorithm integrates advanced computer vision (CV) algorithms to detect, track, and predict pedestrian movements in real time, enhancing safety at a signalized intersection while remaining economically viable and easily integrated into existing infrastructure. Implemented at a key intersection in Bellevue, the CSIC system achieves a 100% pedestrian passing rate while simultaneously minimizing the average remaining walk time after crossings. The algorithm used in this study demonstrates the potential of combining CV with
Xia, RongjingFang, HongchaoZhang, Chenyang
When a train passes continuously over a section of the track, the track gradually moves away from the intended vertical and horizontal alignment with time and repeated use. Regular maintenance on the track, such as leveling, lifting, lining, and tamping, is necessary to maintain the optimal geometry of the track. Ballast is leveled and squeezed by hydraulic rams in tamping machines. The tamping is a process of ballast packing under railway tracks. In current system a set of tungsten carbide chips are attached either by welding or by coating on tamping tool tip made of EN24 steels. These tungsten carbide chips directly come in contact with the ballasts. After few tamping works, gradually these chips torn out and need to be replaced after certain period. Tungsten carbide is a costly material, therefore this research deals with replacement of tungsten carbide with silicon carbide (easily available cheaper) coating used for tamping tools tip. The study consists of microstructural
Mishra, MamtaPandey, ManasSingh, ShrutiSrivastava, SanjayKumar, Jitendra
Considering the large opportunity to reduce net lifecycle carbon emissions through the use of renewable methanol, we address spray technologies needed to overcome the challenge of wall wetting and poor vaporization for methanol and the need for improved computational modeling of these processes. High-speed extinction imaging followed by computed tomography reconstruction is utilized to provide three-dimensional liquid volume fraction for reference fuel injectors, to be used for model validation activities. The first injector is the symmetric 8-hole Spray M injector for the Engine Combustion Network, and the second injector is an asymmetric 6-hole injector designed for lateral-cylinder mounting. The degree of plume interaction and vaporization are characterized at representative injection conditions, showing substantially higher concentrations of liquid for methanol than gasoline even with preheated fuel temperatures (90 degrees C). In light of higher injected mass requirements for
Wan, KevinClemente Mallada, RafaelBuen, ZacharyWhite, LoganOh, HeechangDhanji, MeghnaaPickett, Lyle
This study aims to characterise the flame development for hydrogen-diesel dual direct injection (H2DDI) in an optically accessible heavy-duty engine through high-speed imaging of the natural combustion luminosity. A single hole, side mounted injector was used to inject H2 at 35 MPa in addition to a centrally mounted eight-hole diesel injector providing the ignition source for the H2. Firstly, the diesel pilot flame was examined without H2 to establish the combustion characteristics of the pilot flame. The pilot fuel energy was reduced from 1200 J to 120 J until the minimum repeatable diesel flame was found, which showed a flame distribution that transitioned from an initial quasi-steady diesel flame at peak load (1200 J), to a piston bowl wall-centric flame distribution (840 J) and then to an injector centric flame (120 J). The minimum pilot fuel quantity of 120 J was then used to investigate the ignition process of hydrogen main fuel mixtures supplying 90% energy and only 10% energy
Heaton, AlastarChan, Qing NianKook, Sanghoon
In October 2024, Kongsberg NanoAvionics discovered damage to their MP42 satellite, and used the discovery as an opportunity to raise awareness on the need to reduce space debris generated by satellites. Kongsberg NanoAvionics, Vilnius, Lithuania Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels. Despite this damage, the satellite continued performing its mission without interruption, and we only discovered the impact thanks to an image taken by its onboard selfie camera in October of 2024. It is challenging to pinpoint exactly when the impact occurred because MP42's last selfie was taken a year and a half ago, in April of 2023.
With 2D cameras and space robotics algorithms, astronautics engineers at Stanford have created a navigation system able to manage multiple satellites using visual data only. They recently tested it in space for the first time. Stanford University, Stanford, CA Someday, instead of large, expensive individual space satellites, teams of smaller satellites - known by scientists as a “swarm” - will work in collaboration, enabling greater accuracy, agility, and autonomy. Among the scientists working to make these teams a reality are researchers at Stanford University's Space Rendezvous Lab, who recently completed the first-ever in-orbit test of a prototype system able to navigate a swarm of satellites using only visual information shared through a wireless network. “It's a milestone paper and the culmination of 11 years of effort by my lab, which was founded with this goal of surpassing the current state of the art and practice in distributed autonomy in space,” said Simone D'Amico
Engineers can now capture and predict the strength of metallic materials subjected to cycling loading, or fatigue strength, in a matter of hours, not the months or years it takes using current methods. In a new study, researchers from the University of Illinois Urbana-Champaign reported that automated high-resolution electron imaging can capture the nanoscale deformation events that lead to metal failure and breakage at the origin of metal failure.
Aitech introduced its new artificial intelligence (AI)-enabled picosatellite constellation platform, IQSat, at the 40th annual Space Symposium in April. The platform is designed to bring ready to use commercial off the shelf (COTS) embedded computing to data heavy earth imaging and pattern recognition applications enabled by AI and machine learning (ML) processing and algorithms performed onboard a constellation of IQSats. Available as an individual platform or in constellations that could include thousands of picosatellites, IQSat will become available to customers in the fourth quarter of 2025.
Our MP42 satellite, which launched into low Earth orbit (LEO) two and a half years ago aboard the SpaceX Transporter-4 mission, recently took an unexpected hit from a small piece of space debris or micrometeoroid. The impact created a 6 mm hole, roughly the size of a chickpea, in one of its solar panels.
Image dehazing techniques can play a vital role in object detection, surveillance, and accident prevention, especially in scenarios where visibility is compromised because of light scattering by atmospheric particles. To obtain a high-quality image or as an initial step in processing, it’s crucial to restore the scene’s information from a single image, given that this is an ill-posed inverse problem. The present approach utilized an unsupervised learning approach to predict the transmission map from a hazy image and used YOLOv8n to detect the car from a clear recovered image. The dehazing model utilized a lightweight parallel channel architecture to extract features from the input image and estimate the transmission map. The clear image is recovered using an atmospheric scattering model and given to the YOLOv8n for car detection. By incorporating dark channel prior loss during training, the model eliminates the need for a paired dataset. The proposed dehazing model with fewer
Dave, ChintanPatel, HetalKumar, Ahlad
Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from
Rittenschober, Thomas
In active noise control, the control region size (same meaning as zone of control) decreases as the frequency increases, so that even a small moving of the passenger's head causes the ear position to go out of the control region. To increase the size of the control region, many speakers and microphones are generally required, but it is difficult to apply it in a vehicle cabin due to space and cost constraints. In this study, we propose moving zone of quiet active noise control technique. A 2D image-based head tracking system captured by a camera to generate the passenger's 0head coordinates in real time with deep learning algorithm. In the controller, the control position is moved to the ear position using a multi-point virtual microphone algorithm according to the generated ear position. After that, the multi-point adaptive filter training system applies the optimal control filter to the current position and maintains the control performance. Through this study, it is possible to
Oh, ChiSungKang, JonggyuKim, Joong-Kwan
This study presents a novel methodology for optimizing the acoustic performance of rotating machinery by combining scattered 3D sound intensity data with numerical simulations. The method is demonstrated on the rear axle of a truck. Using Scan&Paint 3D, sound intensity data is rapidly acquired over a large spatial area with the assistance of a 3D sound intensity probe and infrared stereo camera. The experimental data is then integrated into far-field radiation simulations, enabling detailed analysis of the acoustic behavior and accurate predictions of far-field sound radiation. This hybrid approach offers a significant advantage for assessing complex acoustic sources, allowing for quick and reliable evaluation of noise mitigation solutions.
Fernandez Comesana, DanielVael, GeorgesRobin, XavierOrselli, JosephSchmal, Jared
The segment manipulator machine, a large custom-built apparatus, is used for assembling and disassembling heavy tooling, specifically carbon fiber forms. This complex yet slow-moving machine had been in service for nineteen years, with many control components becoming obsolete and difficult to replace. The customer engaged Electroimpact to upgrade the machine using the latest state-of-the-art controls, aiming to extend the system's operational life by at least another two decades. The program from the previous control system could not be reused, necessitating a complete overhaul.
Luker, ZacharyDonahue, Michael
Industrial bearings are critical components in aerospace, industrial, and automotive manufacturing, where their failures can result in costly downtime. Traditional fault diagnosis typically depends on time-consuming on-site inspections conducted by specialized field engineers. This study introduces an automated Artificial Intelligence virtual agent system that functions as a maintenance technician, empowering on-site personnel to perform preliminary diagnoses. By reducing the dependence on specialized engineers, this technology aims to minimize downtime. The Agentic Artificial Intelligence system leverages agents with the backbone of intelligence from Computer Vision and Large Language Models to guide the inspection process, answer queries from a comprehensive knowledge base, analyze defect images, and generate detailed reports with actionable recommendations. Multiple deep learning algorithms are provisioned as backend API tools to support the agentic workflow. This study details the
Chandrasekaran, Balaji
Industries that require high-accuracy automation in the creation of high-mix/low-volume parts, such as aerospace, often face cost constraints with traditional robotics and machine tools due to the need for many pre-programmed tool paths, dedicated part fixtures, and rigid production flow. This paper presents a new machine learning (ML) based vision mapping and planning technique, created to enhance flexibility and efficiency in robotic operations, while reducing overall costs. The system is capable of mapping discrete process targets in the robot work envelope that the ML algorithms have been trained to identify, without requiring knowledge of the overall assembly. Using a 2D camera, images are taken from multiple robot positions across the work area and are used in the ML algorithm to detect, identify, and predict the 6D pose of each target. The algorithm uses the poses and target identifications to automatically develop a part program with efficient tool paths, including
Langan, DanielHall, MichaelGoldberg, EmilySchrandt, Sasha
In single-aisle aircraft, the available storage space for carry-on baggage is inherently limited. When the aircraft is fully booked, it often results in insufficient overhead bin space, necessitating last-minute gate-checking of carry-on items. Such disruptions contribute to delays in the boarding process and reduce operational efficiency. A promising approach to mitigate this issue involves the integration of computer vision technologies with an appropriate data storage system and stochastic simulation to enable accurate and supportive predictions that enhance planning, reduce uncertainty, and improve the overall boarding process. In this work, the YOLOv8 image recognition algorithm is used to identify and classify each passenger’s carry-on baggage into predefined categories, such as handbags, backpacks, and suitcases. This classified data is then linked to passenger information stored in a NoSQL database MongoDB, which includes seat assignments and the number of carry-on items
Bergmann, JacquelineHub, Maximilian
The process of producing aircraft parts involves the drilling of aluminum alloys. This creates a large amount of chips, which are removed using air, but sometimes they still remain within the holes. This is checked by inspectors through visual inspection. However, the quality of human inspection varies based on skill level and fatigue. Thus, image-based inspection should be used to stabilize and further improve inspection quality. This study aims to build a framework for chip detection based on image processing. Taking into account on-site implementation, the system must have low installation and running costs and be standalone. Therefore, we adopt the KIZKI algorithm, which satisfies these conditions. KIZKI means awareness in Japanese. This is a model of human peripheral vision and saccades. It does not require training like AI and can achieve high-speed and high-performance detection using a low-performance computer. In other words, there is no need for a computer with an expensive
Iinuma, MarinSato, JunyaTsuji, Masahiko
Innovators at NASA Johnson Space Center have developed a handheld digital microscope to fill the critical microscopy needs of human space exploration by providing flight crews in situ hematological diagnostic and tracking ability to assess and monitor crew health in the absence of gravity. Although currently in use aboard the International Space Station (ISS) to work in conjunction with NASA’s handheld slide staining system, the microscope may have numerous applications here on Earth.
Machining metal has its challenges as many shops will attest, but machining glass is another matter – one that Dan Bukaty Jr., President of Precision Glass & Optics (PG&O) is well schooled in. Mr. Bukaty and his 35-person shop manufacture high-end precision glass optics for customers such as IMAX, Intuitive Surgical, Boeing and NASA, to name a few. The products PG&O make can range from the ordinary to the extraterrestrial, such as mirrors that it fabricated for the Hobby–Eberly Telescope to measure dark energy in outer space.
Metabolic imaging is a noninvasive method that enables clinicians and scientists to study living cells using laser light, which can help them assess disease progression and treatment responses. But light scatters when it shines into biological tissue, limiting how deeply it can penetrate and hampering the resolution of captured images.
New technology developed by researchers at the University of Houston could revolutionize medical imaging and lead to faster, more precise and more cost-effective alternatives to traditional diagnostic methods.
The efficiency and performance of lithium-ion batteries are highly influenced by the quality of laser cutting of electrode materials. The laser cut quality of thin foils is often measured by amount of kerf width and heat-affected zone (HAZ). This article adopts a novel approach that involves pre-cooling of thin copper foils prior to the laser cutting process. The impact of laser conditions and foil temperature were analyzed on HAZ and kerf width induced during laser cutting experiments conducted based on L27 orthogonal array. Teaching–learning–based optimization (TLBO) technique was employed to identify the optimal laser parameters. ANOVA results indicated that the temperature was the most significant factor influencing kerf width and HAZ. The optimized laser parameters identified through TLBO technique were 16 W laser power, 69.47 mm/s scanning speed, and 20 kHz pulse frequency at dry ice conditions. A reduction of 50.76% kerf width and a decrease in 7.6% HAZ were observed when the
Rao, Akshay P.Bharatish, A.Solaiachari, SivakumarKumar, S. Mahendra
Platinum (Pt), palladium (Pd), and rhodium (Rh) are used as active substances in exhaust gas purification catalysts for automobiles. Among these, Rh is an essential element because it efficiently promotes a NOx reduction reaction. On the other hand, the price of Rh has been rising in recent years. From the perspective of the supply risk of rare resources, there is an urgent need to develop technologies to replace or reduce the amount of Rh used in catalysts. We focused on the pseudo-rhodium alloy developed by the ACCEL program of the Japan Science and Technology Agency (JST), and then investigated the application of the pseudo-rhodium alloy on the catalysts of our motorcycles and also the degradation process. A nanosized PdRuIr alloy supported on a ceria-zirconia solid solution (PdRuIr/CZ) was prepared and assembled into a motorcycle for emissions measurement. The PdRuIr/CZ catalyst with an alloy loading of 4.0 g/L had initial properties comparable to the Rh supported on a CZ (Rh/CZ
Motegi, TakuyaTatara, ShunyaTakamoto, ShunpeiDoi, Kosuke
Urea SCR system, installed in diesel engine vehicles such as trucks and agricultural machinery, is widely used as an exhaust gas aftertreatment system that efficiently purifies NOx, an environmentally harmful substance. Furthermore, the Urea SCR systems may be installed in hydrogen/carbon-neutral fuel engines, and biofuel aircraft engines aiming to achieve carbon neutrality. However, an important problem is the degradation of NOx purification performance caused by urea crystallization due to an undesired reaction of urea water solution (UWS) and clogging of the exhaust pipe due to the formation of deposits caused by an unknown number of atomized UWS behaviors, mainly during idling and low-speed operation when the pipe temperature is relatively low. The problem is that the UWS behavior of the atomized UWS is not well understood. To solve these problems, it is necessary to clarify the complex two-phase flow phenomenon of gas and droplets in the exhaust pipe, which is still unknown. We
Ono, JoeNohara, TetsuoNara, ShotaroKawamoto, YukiFukushima, NaoyaOchiai, Masayuki
The emulsified fuel is mixed base fuel with water and stabilized by surfactant. The advantage of emulsified fuel is the improvement of spray and mixture formation by the secondary atomization. The secondary atomization means that the sprayed fuel droplets in cylinder would occur the atomization because of the difference of boiling points between base fuel and water. It is expected improving combustion efficiency and suppressing toxic emissions such as NOx and PM in small diesel engine [1]. The behavior of an emulsified fuel droplet in heating process has 3 types, Namely the micro-explosion, the puffing and only vaporizing without atomization. Their timing and behavior are influenced on the concentration of surfactant within an emulsified fuel droplet. However, it is difficult to determine the concentration. This paper focuses on the determination of the concentration by engineering evaluation. Our previous reports have reported that the evaluation for the atomization timing of an
Kurahashi, YutaKatsuki, HiromuTanaka, Junya
With the growing diversification of modern urban transportation options, such as delivery robots, patrol robots, service robots, E-bikes, and E-scooters, sidewalks have gained newfound importance as critical features of High-Definition (HD) Maps. Since these emerging modes of transportation are designed to operate on sidewalks to ensure public safety, there is an urgent need for efficient and optimal sidewalk routing plans for autonomous driving systems. This paper proposed a sidewalk route planning method using a cost-based A* algorithm and a mini-max-based objective function for optimal routes. The proposed cost-based A* route planning algorithm can generate different routes based on the costs of different terrains (sidewalks and crosswalks), and the objective function can produce an efficient route for different routing scenarios or preferences while considering both travelling distance and safety levels. This paper’s work is meant to fill the gap in efficient route planning for
Bao, ZhibinLang, HaoxiangLin, Xianke
While numerous advancements have been made in autonomous navigation for structured indoor and outdoor environments, these solutions often do not generalize well to off-road settings. There are unique challenges in such settings such as unreliable GPS, limited computational and memory resources, and sparse environmental features, making navigation particularly difficult. In our work, we propose a novel data structure called Hierarchical Dynamic Scene Graphs (HDSG) to address these challenges. HDSG captures environmental information at different resolutions, integrating both geometric and semantic features. It enables various navigation tasks such as localization, loop closure, and human interaction through the visualization of environmental features for remote operators. We evaluated the performance of localizing a robot’s position within the world frame by comparing compact spatial descriptors extracted from semi-consecutive scene graphs, derived from 3D LiDAR point clouds. Compared to
Alam, Fardifa FathmiulLuricich, FedericoLi, NianyiJia, YunyiLi, Bing
This paper explores the integration of two deep learning models that are currently being used for object detection, specifically Mask R-CNN and YOLOX, for two distinct driving environments: urban cityscapes and highway settings. The hypothesis underlying this work is that different methods of object detection will work best in different driving environments, due to the differences in their unique strengths as well as the key differences in those driving environments. Some of these differences in the driving environment include varying traffic densities, diverse object classes, and differing scene complexities, including specific differences such as the types of signs present, the presence or absence of stoplights, and the limited-access nature of highways as compared to city streets. As part of this work, a scene classifier has also been developed to categorize the driving context into the two categories of highway and urban driving, in order to allow the overall object detection
Patel, KrunalPeters, Diane
Off-road vehicles are required to traverse a variety of pavement environments, including asphalt roads, dirt roads, sandy terrains, snowy landscapes, rocky paths, brick roads, and gravel roads, over extended periods while maintaining stable motion. Consequently, the precise identification of pavement types, road unevenness, and other environmental information is crucial for intelligent decision-making and planning, as well as for assessing traversability risks in the autonomous driving functions of off-road vehicles. Compared to traditional perception solutions such as LiDAR and monocular cameras, stereo vision offers advantages like a simple structure, wide field of view, and robust spatial perception. However, its accuracy and computational cost in estimating complex off-road terrain environments still require further optimization. To address this challenge, this paper proposes a terrain environment estimating method for off-road vehicle anticipated driving area based on stereo
Zhao, JianZhang, XutongHou, JieChen, ZhigangZheng, WenboGao, ShangZhu, BingChen, Zhicheng
Vehicle ADAS Systems majorly comprises of two functions: Driving and Parking. The most common form of damage to the vehicle which goes unnoticed with unidentified cause are parking damages. A vehicle once parked at a certain location may get damaged without knowledge of the user. In this work developed a solution that not only pre-warns the driver but also prepares the vehicle beforehand if it suspects a damage may occur. This eliminates the latency between damage and information capture, detects small damages such as scratches, classifies the type of damage and informs the user beforehand. This is solution is different from our competitors as the existing solutions informs the user about the scratches/damages, but these solutions are expensive, have high response time, and the damage information is captured after the damage has occurred. The solution consists of the following check blocks: Precondition, Sensor Control and Action Module. The Precondition Module observes the vehicle
Debnath, SarnabPatil, PrasadBelur Subramanya, SheshagiriGovinda, Shiva Prasad
Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the
Perera, NishanGriffiths, HarrisonPrentice, Greg
This study experimentally investigates the liquid jet breakup process in a vaporizer of a microturbine combustion chamber under equivalent operating conditions, including temperature and air mass flow rate. A high-speed camera experimental system, coupled with an image processing code, was developed to analyze the jet breakup length. The fuel jet is centrally positioned in a vaporizer with an inner diameter of 8mm. Airflow enters the vaporizer at controlled pressures, while thermal conditions are maintained between 298 K and 373 K using a PID-controlled heating system. The liquid is supplied through a jet with a 0.4 mm inner diameter, with a range of Reynolds numbers (Reliq = 2300÷3400), and aerodynamic Weber numbers (Weg = 4÷10), corresponding to the membrane and/or fiber breakup modes of the liquid jet. Based on the results of jet breakup length, a new model has been developed to complement flow regimes by low Weber and Reynolds numbers. The analysis of droplet size distribution
Ha, NguyenQuan, NguyenManh, VuPham, Phuong Xuan
Videos from cameras onboard a moving vehicle are increasingly available to collision reconstructionists. The goal of this study was to evaluate the accuracy of speeds, decelerations, and brake onset times calculated from onboard dash cameras (“dashcams”) using a match-moving technique. We equipped a single test vehicle with 5 commercially available dashcams, a 5th wheel, and a brake pedal switch to synchronize the cameras and 5th wheel. The 5th wheel data served as the reference for the vehicle kinematics. We conducted 9 tests involving a constant-speed approach (mean ± standard deviation = 57.6 ± 2.0 km/h) followed by hard braking (0.989 g ± 0.021 g). For each camera and brake test, we extracted the video and calculated the camera’s position in each frame using SynthEyes, a 3D motion tracking and video analysis program. Scale and location for the analyses were based on a 3D laser scan of the test site. From each camera’s position data, we calculated its speed before braking and its
Flynn, ThomasAhrens, MatthewYoung, ColeSiegmund, Gunter P.
Photogrammetry is a commonly used type of analysis in accident reconstruction. It allows the location of physical evidence, as shown in photographs and video, and the position and orientation of vehicles, other road users, and objects to be quantified. Lens distortion is an important consideration when using photogrammetry. Failure to account for lens distortion can result in inaccurate spatial measurements, particularly when elements of interest are located toward the edges and corners of images. Depending on whether the camera properties are known or unknown, various methods for removing lens distortion are commonly used in photogrammetric analysis. However, many of these methods assume that lens distortion is the result of a spherical lens or, more rarely, is solely due to distortion caused by other known lens types and has not been altered algorithmically by the camera. Today, several cameras on the market algorithmically alter images before saving them. These camera systems use
Pittman, KathleenMockensturm, EricBuckman, TaylorWhite, Kirsten
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