Browse Topic: Electronic equipment
New technologies, advanced materials, evolving mission profiles and fast-changing requirements are forcing the aerospace and defense (A&D) industry to dramatically increase the speed of engineering. Companies must design, validate and bring more complex products to market faster than ever, even as software, electronics and autonomy continue to reshape what aircraft, spacecraft and defense systems can do. At the same time, a growing production challenge is emerging. Workforce shortages, supply chain disruption and pressure to reduce cost and cycle time are converging with new demands for greater volume and flexibility. Defense programs are seeing increasing need for larger quantities of lower-cost systems such as drones, while commercial aerospace companies continue to work through backlogs and reinforce their fleets. To keep pace, the industry must accelerate innovation while also scaling production with greater speed, resilience and adaptability.
In military and aerospace systems, thin film patterned substrates literally serve as the foundation of some of the most critical electronic assemblies, including radio frequency (RF), microwave, millimeter wave, and high-speed digital circuits. These substrates are typically made by depositing extremely thin layers of conductive and dielectric materials on bases built from materials like alumina, aluminum nitride, quartz, or certain high-performance titanates with various dielectric constants up to a k of 4,000.
With the increasing demand for material microimaging analysis, there is a growing need for advanced precision grinding and polishing equipment, especially for metals, ceramics, and composites. Existing automated systems struggle with handling complex material challenges. This paper presents a fully automated adaptive grinding and polishing machine based on an STM32 microcontroller that handles multi-material samples. The system includes modules for sample access, cleaning, pad replacement, human-computer interaction, and equipment communication. The STM32 microcontroller executes grinding and polishing tasks based on instructions from the host computer while dynamically adjusting PID control parameters using an improved weighted average optimization algorithm. This approach enhances control accuracy, stability, and overall surface treatment quality compared to traditional PID control methods.
To solve a problem that ignition anomaly can’t be detected in time, based on the thermal equilibrium equation, the space heat flow, heater heating, propellant combustion, and thermal radiation to cryogenic space are considered to build an accurate ignition temperature method for the 10 N thruster by using on-orbit true temperature. Further, considering the error of measuring the thermistor, an envelope model for the 10 N thruster ignition temperature is established. Based on the above, a detection method for the 10 N thruster ignition anomaly of on-orbit satellites is proposed. The accuracy of the method is relatively high, and the absolute error is less than 3 degrees Celsius. An anomaly can be quickly detected when the 10N thruster ignition temperature deviates from the normal trend by 3–5 degrees celsius. The method is applied to a DFH-3 satellite, and the maximum difference of 10 N thruster ignition temperature between the theoretical values calculated by the proposed method and the measured values is only 2.72 degrees celsius. It has been proven that the prediction accuracy of the proposed method is high. It plays an important role in discovering the 10N thruster ignition anomaly in time and ensuring the success of satellite orbit or attitude control.
The detection of free space plays a fundamental role in ensuring the safe and efficient operation of heavy-duty vehicles, particularly in environments where the available area to maneuver is severely constrained, such as construction zones, rest areas, or loading docks. An accurate estimation of free space is essential to prevent collisions, maintaining operational continuity and minimizing vehicle downtime. As observed from the reviewed literature, despite the large number of proposed free-space detection methods, there is no concise and established definition about how free space should be determined, represented, and inferred, nor agreement on the semantic classes to be considered. This heterogeneity complicates systematic comparison and benchmarking across approaches. This paper presents a structured survey and methodological analysis of recent free-space detection and semantic segmentation approaches across automotive LiDAR-, camera-, and radar-based perception systems, as well as multimodal sensor fusion. The review spans classical geometric and occupancy-based techniques together with deep-learning methods, along with datasets commonly used for evaluation. The main contributions are (i) a structured taxonomy and comparative analysis of existing free-space definitions and detection strategies, categorized by their assumptions, representation forms, and sensing modalities; and (ii) a unified and application-independent definition of free space together with the required semantic classes. These contributions aim to provide a consistent conceptual foundation to support future research and to aid the systematic evaluation of upcoming free-space detection systems.
Medical device manufacturing is undergoing a structural shift. As devices become smaller with broader functionality, traditional approaches to assembling electronics are no longer sufficient. Increasingly, performance, durability, and reliability are dictated not just by design, but by how that design is manufactured.
Physical AI refers to applications in which AI technologies are connected to hardware that sense and execute actions in the physical world, allowing systems to autonomously act and adapt in real time. It spans automotive, robotics, industrial automation, smart infrastructure, aerospace, healthcare devices, software-defined machines, and more. Regardless of application, they have one thing in common: they must operate safely, reliably, and predictably in real world environments. Unlike purely digital AI, these systems are constrained by embedded electronics, timing, power, safety, and system-level interactions that are difficult to validate early.
Acoustic user interfaces and audio experiences are among the leading comfort factors in new vehicle interior designs. OEMs are more and more focusing on loudspeaker design and positioning, to provide the most immersive experience to the customers. The industrial target is to be able to predict the performance of an audio system in early design phases. This paper presents an integrated vibro-acoustic methodology enabling early-stage prediction of loudspeaker performance in real vehicle conditions. The approach combines electromechanical characterization, a hybrid loudspeaker calibrated model valid across the audible range and coupled FEM/BEM/SEA simulations to capture the loudspeaker response in the vehicle’s cabin considering door-installation effects and cabin acoustics. The method is validated experimentally on a rear-door loudspeaker installed in a production vehicle, showing strong correlation with measured SPL. A final application case demonstrates its capability to assess the impact of alternative speaker mounting positions during the design phase.
As computer chips continue to get smaller and more complex, the ultrathin metallic wires that carry electrical signals within these chips have become a weak link. Standard metal wires get worse at conducting electricity as they get thinner, ultimately limiting the size, efficiency, and performance of nanoscale electronics.
A sweat-powered wearable has the potential to make continuous, personalized health monitoring as effortless as wearing a Band-Aid. Engineers at the University of California San Diego have developed an electronic finger wrap that monitors vital chemical levels — such as glucose, vitamins, and even drugs — present in the same fingertip sweat from which it derives its energy.
In a world first, researchers have used 2D materials, which are only an atom thick and retain their properties at that scale, unlike silicon, to develop a computer capable of simple operations. The development, published June 11 in Nature, represents a major leap toward the realization of thinner, faster and more energy-efficient electronics, the researchers said. They created a complementary metal-oxide semiconductor (CMOS), which is at the heart of nearly every modern electronic device, without relying on silicon. Instead, they used two different 2D materials to develop both types of transistors needed to control the electric current flow in CMOS computers: molybdenum disulfide for n-type transistors and tungsten diselenide for p-type transistors.
Keith Yuen, a supervisory engineer at Naval Air Warfare Center Weapons Division (NAWCWD) spent years building a jammer designed to defeat America’s own radars. The harder his team made it for friendly pilots to see through the jamming, the better they were doing their job.
Ultra-miniature sensors are enabling advanced procedures and treatments across a wide range of medical devices, from catheters and neuro interfaces to wearables. But as electromagnetic sensors get smaller, trade-offs begin to emerge — lower sensitivity, less tolerance for environmental influences, and greater susceptibility to interference — underscoring the need for robust testing to ensure accurate, reliable tracking.
Designing the next generation of wireless wearables, implantables, and real-time external or in-body monitoring devices is a complex challenge that requires highly reliable electronic components that greatly exceed the performance of standard commercial alternatives.
Anyone who has ever been frustrated by an overheating mobile phone or wondered how devices will withstand the heat generated by artificial intelligence (AI) applications may be excited to learn about a recent discovery that challenges long-standing assumptions about cooling pathways in electronics.
Researchers at the University of California, Irvine, and New York’s Columbia University have embedded transistors in a soft, conformable material to create a biocompatible sensor implant that monitors neurological functions through successive phases of a patient’s development.
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential speed. The overall design satisfies the requirements of safety and strength through mechanical verification and stress analysis. The proposed system can help the elderly people to recover from falls better and enhance their independence and safety in their daily walks.
A boat can sink in under a minute, stranding passengers miles from land and leaving them virtually invisible amid the vast expanse of water. Survival can depend on emergency supplies such as a personal locator beacon (PLB) and emergency position-indicating radio beacon (EPIRB) to alert search and rescue teams. When a competitive fishing trip went wrong for Easton Barrett and his friends 40 miles off the Gulf Coast of Mississippi in 2024, a PLB helped the U.S. Coast Guard rescue the people clinging to coolers and treading water after being head-butted by sharks.
This paper presents a study of gunshot acoustic signal detectability in the near field of propeller noise, with a focus on the isolation of external gunshot signatures masked by propeller-induced noise. Controlled measurements were conducted in a Recirculation Delayed Anechoic Chamber (RDAC), where acoustic data were collected across varying rotor speeds, source locations, and propagation distances. Propeller noise characteristics were verified using UCD-QuietFly. The recorded signals were analyzed for the acoustic pressure, sound pressure level, and overall sound pressure level directivity to quantify masking effects. Results show that RPM is the dominant factor governing signal detectability. At 3000 RPM, the gunshot signal remains clearly identifiable within the low frequency range of 200–2000 Hz. At 4000 RPM, the signal becomes partially masked, while at 5000 RPM, propeller noise fully dominates and the gunshot signal becomes undetectable. Detectability is further reduced with increasing propagation distance. In-plane microphone locations provide improved detectability. A machine learning-based spectral separation framework was developed to suppress propeller noise and enhance the visibility of impulsive gunshot signatures in multichannel spectrograms. Experimental results show that learning-based denoising is effective at lower RPMs where the signal-to-noise ratio remains favorable, but performance degrades as broadband masking intensifies at higher rotor speeds.
With the increasing demand for underwater and implantable medical electronics, a stable and continuous power supply is essential. However, conventional wireless charging methods (such as electromagnetic induction and radio frequency-based charging) used in smartphones and wireless earphones suffer from short transmission distances, low energy transfer efficiency in biological tissues, and electromagnetic interference. To overcome these limitations, researchers are now considering the use of ultrasound as a new wireless power transfer technology. Ultrasound has the advantage of being human-friendly and less absorbed by tissues, allowing for more reliable energy transfer in implantable and skin-adherent devices. As a result, wireless charging technology utilizing ultrasonic energy is emerging as the next generation of power transfer.
Scientists are striving to discover new semiconductor materials that could boost the efficiency of solar cells and other electronics. But the pace of innovation is bottlenecked by the speed at which researchers can manually measure important material properties.
A University of Houston engineer has developed a method to detect possible damage in concealed cold-formed steel construction framing materials hidden behind walls, without having to tear the walls open.
As interest in wearable technology has surged, research into creating energy-storage devices that can be woven into textiles has also increased. Researchers at North Carolina State University have now identified a “sweet spot” at which the length of a threadlike energy storage technology called a “yarn-shaped supercapacitor” (YSC) yields the highest and most efficient flow of energy per unit length.
A new transceiver invented by electrical engineers at the University of California, Irvine boosts radio frequencies into 140-gigahertz territory, unlocking data speeds that rival those of physical fiber-optic cables and laying the groundwork for a transition to 6G and FutureG data transmission protocols.
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