Browse Topic: Frames
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both frames. The application of the proposed transformation maps the co-rotating branches onto the inertial observations, yielding consistent forward/backward splitting between the two measurement systems.
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages—sensor acquisition, video encoding, data transmission, decoding, and display—undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software boundaries. Evaluations demonstrate a latency reduction from a baseline of 45.3 milliseconds to an optimized 23.5 milliseconds, representing a 48.1% improvement without sacrificing spatial resolution or detection robustness. Under optimized configurations, the framework sustains frame rates above 60 FPS at both Full HD and 4K resolutions, with frame drop rates held to approximately 3%. Perceptual evaluation further confirms that object detection accuracy consistently exceeds 91% within the <35 ms latency range, while collision-prediction delays are reduced to below 12.4 ms, ensuring timely responses in dynamic scenarios. These improvements collectively validate the critical importance of hardware-software co-design for embedded vision systems. The results highlight that ultra-low-latency perception is achievable on edge platforms when pipelines are designed with cross-layer optimization, bridging sensor interfaces, video codecs, network transport, and GPU computation. The proposed architecture provides a scalable foundation for future embedded vision deployments in autonomous driving, robotics, and unmanned aerial systems, where low latency is a non-negotiable requirement for safety, reliability, and operational efficiency.
This paper proposes HaloBus, an innovative, edge-computing solution designed to mitigate this risk by detecting student boarding and exiting in real time using lightweight AI based methods. A persistent challenge in elementary school transportation is the issue of missing students after they exit their buses, which disproportionately impacts low-income households. Current safety systems place the burden of implementation on individual households, often requiring independent methods. Common methods include applications on a personal device or a small tracker. However, not everyone can afford these options, and ensuring child safety is a primary concern for parents and caregivers. That is why HaloBus was invented. The system employs YOLOv5us—an Ultralytics-enhanced, anchor-free, split-head architecture that offers a superior accuracy speed trade-off. By providing real-time, on-device alerts, HaloBus enables immediate intervention to prevent a student from being left behind, thereby shifting the focus from reactive post-incident response to proactive safety. Trained on over 70,000 labeled and unlabeled images, the model can accurately detect multiple students simultaneously, significantly reducing false positives. In real-world deployment, the model sustained 30 frames per second on the Raspberry Pi and achieved detection confidence levels exceeding 75% even when subjects wore sunglasses or hoodies. With opt-in participation for each family, HaloBus effectively balances detection efficiency and privacy protection. Overall, HaloBus offers a low-cost, scalable, and ethically conscious approach to enhancing school-bus safety by delivering reliable, on-device boarding and exit detection for multiple students in varied real-world conditions.
The timing of video recordings, along with the spatial positioning of objects, is a fundamental parameter for calculating the speed time history. If the task involves determining the average speed of an object moving at approximately constant speed, it may be acceptable to average the speed over several to a dozen frames, using the fps (frames per second) parameter as the basic time unit.. However, if the objective is to compute speed from individual frames, the reliability of the timing becomes crucial. Without access to DVR hardware documentation, proprietary algorithms, or software – and considering the frequent hardware modifications and software updates - the most effective way to solve the problem is through a reverse-engineering approach. This study discusses several aspects of timing analysis, including: (1) making a test recording of a calibrated LED lightboard; (2) analyzing the relationship between the lightboard time and the presentation time stamp (pts) extracted from the file metadata; (3) investigating frame skipping and frame timing errors due to frame rate changes; (4) modeling the composite motion of the rolling shutter and the lightboard LEDs; (5) identifying the DVR’s actual frame capture rate; and (6) compensating the timing of the evidentiary recording. Establishing the timing scheme of the test recording enables reliable speed analysis based on two or three adjacent frames of the evidentiary recording, as well as the determination of the velocity time history over a short segment of the recording.
This paper carried out the fire failure analysis of valve-regulated lead-acid battery in communication equipment room. Through disassembly and observation of the battery and iron frame of battery cabinet in the area of fire origin, we obtained the key residual traces and used the physical and chemical analysis methods such as macroscopic/microscopic morphology, EDS, X-ray and metallographic, it was finally judged that the leakage of the battery electrolyte lead to the connection of the battery electrode plate and the iron frame and subsequently the electric heating fault caused the fire accident. Furthermore, we put forward some suggestions according to the existing problems, which may contribute to the prevention of similar failures.
Bogie frame is a main skeleton and structural member in railway system which is carrying all the loads such as Suspensions, Axles, wheels, car body, Motor, Gear box etc. The frame is subjected an exceptional and service stresses in Vertical, Longitudinal, Lateral and twist directions throughout the service life which should be withstand for a life span of 30 years without failure. The purpose of this project is to determine the Structural integrity of the Metro rail bogie frame in consideration with EN13749 standard. This paper is the outcome of bench testing of metro rail bogie frame with the application of multiaxial loading in static and dynamic campaign through which stress data is collected with strain gauge sensors and correlated with the FEA results at initial design phase. This helps to verify and evaluate the design and validate the quality of metro rail frame as per the requirement specified in EN13749:2021 European standard in early design stages.
According to a problem of the vibration and noise suppression of an engineering vehicle cab, a dynamical model of the engine-frame-cab system was established to describe the vibration transmission path. The method of calculation of the vibratory power flow, which is transmitted from the vibration source engine to the cab through the frame and isolators, was deduced. And then an optimization strategy for the frame structure and the corresponding analysis algorithm process were proposed based on the objective function of power flow. The method proposed was validated through an application to a practical example, which would have practical value in the field of vehicle vibration reductions and optimization design of frame structures.
By its seventh flight after the first take-off, the RACER (Rapid And Cost-Effective Rotorcraft) demonstrator smoothly reached the targeted 220kts speed in stabilized forward flight, validating the high-speed compound architecture developed by Airbus Helicopters in the frame of Clean Sky 2 programme. During the flight envelope exploration, the dynamic behavior of the main rotor was carefully assessed, by monitoring the vibratory loads and validating its aeroelastic stability. Particular care was taken to validate the predicted stability domain of the Dual Rotor phenomenon, a particular case of flap-lag coupling associated with high-speed flight conditions. This paper presents the most significant results shaping the success of RACER flight test campaign. After having introduced the theoretical background and the associated analytical equations, the simulation framework based on the comprehensive analysis tool STORM is presented to discuss the numerical resolution of the stability problem. Then, the rotor dynamics loads and airframe vibratory behavior of RACER are closely examined to demonstrate the absence of any sign of instability, in the various flight conditions offered by its rotor and wing configuration. At last the flight test results are compared to the computed stability domain to assess the margins and estimate the high-speed potential of the rotorcraft.
Developed in the frame of the European Clean Sky 2 program, the RACER High Speed Helicopter Demonstrator of Airbus performed its maiden flight on April 25th, 2024. In the continuity of the previous high-speed demonstrator X3 (1st flight in 2010) the RACER is a 7/8t (15000 / 18000 lb) class compound helicopter powered by two SHE Aneto-1X engines, including a wing and two propellers. The tail rotor is removed as the two propellers control the yaw axis by differential thrust. At flight 07, with its initial default settings, it reached a true airspeed of 227 kts in level flight, exceeding its objective of 220 kts.
Mechanical light detection and ranging (LiDAR) units utilize spinning lasers to scan surrounding areas to enable limited autonomous driving. The motors within the LiDAR modules create vibration that can propagate through the vehicle frame and become unwanted noise in the cabin of a vehicle. Decoupling the module from the body of the vehicle with highly damped elastomers can reduce the acoustic noise in the cabin and improve the driving experience. Damped elastomers work by absorbing the vibrational energy and dispelling it as low-grade heat. By creating a unique test method to model the behavior of the elastomers, a predictable pattern of the damping ratio yielded insight into the performance of the elastomer throughout the operating temperature range of the LiDAR module. The test method also provides an objective analysis of elastomer durability when exposed to extreme temperatures and loading conditions for extended periods of time. Confidence in elastomer behavior and life span was restored when no signs of performance degradation were present after 30 simulated years of normal loading conditions at extreme temperatures.
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 reflected sound. The measurement instrumentation uses a rotating linear array of a few digital microphones which granularly scans the incident sound field on a circular area. The proposed method for computing an acoustic image is based on compensating the moving microphone signals for Doppler distortions and evaluating the coherence of the resulting signals with a non-moving reference microphone for each point in the acoustic image. The methodology is evaluated in the context of localizing the periodic engage event of an electromechanical clutch and the clicking noise of the aluminium frame of a passenger car seat under periodic excitation.
The weave mode of a motorcycle is known to be affected by the flexibility of the vehicle frame. The weave mode has been shown to be more unstable in the 10-DOF model than in the 4-DOF model. However, it is not clear why the weave mode would be unstable, given the six different frame flexibilities. In this study, the authors analyzed the stability of the weave mode in a 4-DOF model when the same was integrated with two types of frame flexibilities. In the vehicle specifications used in the analysis, the combination of the bending flexibility of the front forks and the torsional flexibility of the main frame destabilizes the weave mode. The analysis results show that the phase delay of the front tire lateral force is caused by the phase delay of the steering angle. The combined bending flexibility of the front forks and the torsional flexibility of the main frame results in a large phase lag in the steering angle.
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