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Connectors: High-current DC power in compact design

Amphenol Industrial Products Group now offers a versatile connection system that distributes high-current DC power in a compact design. Designed to connect wire to wire, wire to board, and busbar terminations, the Amphe-PD series distributes higher currents with less heat than similar-sized connectors on the market. Ideal for use in datacenter equipment, robotics, and industrial automation, the Amphe-PD series connectors offer wire terminations ranging from 12 AWG to 4 AWG.
Click here to learn more.

Cool Tools: Wireless digital micrometer

The new 40 EWRi is the latest addition to Mahr's Integrated wireless family of products, including digital calipers, indicators, and depth gages, which allow users to measure faster, more easily, and more reliably. Measurement data is transferred to an i-Stick on a computer without any interfering data cables, and MarCom software makes data acquisition simple: Just take a measurement and transmit measuring data directly into MS Excel or via a keyboard code into any Windows program or existing SPC application.
Click here to learn more.

EMI shielding gaskets offered in many materials

Tech-Etch offers EMI shielding D-Connector gaskets in a wide variety of materials. Five standard sizes of 9-, 15-, 25-, 37-, and 50-pin configurations are available in Stainless Steel; Beryllium Copper; X-, Y-, Z-axis Conductive Foam; and Metalized Fabric consisting of a metalized fabric over a polyurethane foam core. Additionally, four conductive elastomers fill out the D-Connector product line: Series 1000 Supershield silicone elastomer filled with conductive metal particles; Series 4000 Multishield composite material environmental seal; Series 5000 Monoshield for applications where the gasket is limited to 0.02-in. thickness and gap irregularities do not exceed 0.003 in.; and Series 5500 Weaveshield composite (woven aluminum wire screen impregnated with either a neoprene or silicone elastomer), and EMI shielding and pressure seal gasket material used for very small gaps. Custom gaskets can be manufactured.
Click here to learn more.

Wi-Fi high-temp air flow monitor for hazardous environments

Wind Probe LLC has introduced a high-temp air flow monitor Wi-Fi instrument for large- and small-size ovens. This instrument combines the latest advances in materials, process control, and microprocessor technology and hardware and software design. The model 200 is small, lightweight, and suitable for harsh environments seen in high-temperature curing ovens. One of the most exciting markets includes air flow monitoring at 200 deg C in carbon composite honeycomb ovens. The software permits selecting data rates and running averaging in both temperature and air flow. The software is easily updated, and reference tables can be uploaded using the RS-232 communications interface.
Click here to learn more.

New Canfield Connector magnetic sensor adds reliability and safety to vehicles, machines, systems

The rugged Series CS Cylindrical Threaded Mount Sensor from Canfield Connector senses magnetism and triggers action in a variety of applications. The sensor’s first field application equips a cement truck, where it picks up a signal from a magnet mounted to the mixing drum and controls how much the drum rotates. In an industrial automation setting, the sensor can detect the closure of a door and allow a machine to run, enhancing safety. The CS Sensor can also react to magnetism that identifies changes in liquid levels or positions of parts in a wide range of vehicles, machines, and systems.
Click here to learn more.

Industrial cybersecurity for small and medium-size businesses

The International Society of Automation, at the request of the U.S. Department of Homeland Security, has developed a white paper designed to help small and medium-sized businesses (SMBs) recognize their vulnerability to industrial cyberattack and forge an effective cybersecurity plan based on established standards and practices. “Industrial Cybersecurity for Small and Medium Sized Businesses: A Practical Guide” leverages ISA’s in-depth knowledge of industrial automation and control systems (IACS) and subject-matter expertise in industrial cybersecurity.
Get this valuable resource.

SNAP-TOP fasteners hold printed circuit boards securely without mating screws

New PEM SMTSS ReelFast SNAP-TOP standoff fasteners from Penn-Engineering hold printed circuit boards securely in assemblies without requiring mating screws or other loose threaded hardware to complete attachment. These unthreaded standoffs promote streamlined production by easily installing in boards in the same manner and at the same time as other surface-mount components prior to the automated reflow solder process. They ultimately enable precise and reliable mounting and spacing of boards using less hardware and fewer operations.
Click here to learn more.

FUTEK mini load cells take on Shark Week

On the Discovery Channel’s special “Shark School with Michael Phelps” last week, the team engineers at Peacock Productions used three FUTEK Donut/Through Hole load cells as well as FUTEK instrumentation to test a great white shark’s bite force. The three LTH500 Donut/Through Hole Load Cells were placed in a special mold that mimicked the shark's prey. By combining the IHH500 Digital Hand Held Display and IAC200 4 Channel Summing Junction Box with the load cell setup, the production team was able to accurately measure the force of the great white shark's bite, which registered at 10,000 Newtons -- equivalent to a car crashing into a wall at 100 mph! The force reading was unprecedented; it was the first shark bite to register above 6,000 Newtons.
Check out the FUTEK setup for the Discovery Channel's "Shark School."
Watch the Discovery Channel's bite tester in action.

Everything you wanted to know about heatsinks

How well a heatsink performs depends on particular aspects of its design, such as the thermal conductivity of the material it's made of, its overall dimensions, fin type used, airflow rate, and system. A theoretical model can be used to predict performance, or it can be measured experimentally. But because of the complex 3D nature of today’s electronic systems, engineers often use the numerical method via computational fluid dynamics (CFD) to determine the thermal performance of a heatsink before prototyping. This informative blog post from Mentor features two on-demand webinars to run through the basics of heatsink design and considerations.
Read the Mentor blog on heatsink design.

Mike Likes: Unit Conversion Tool

Convert popular spring units such as force or retaining ring thrust capacities into metric units with Smalley’s engineering tools. Convert units such as mass and weight, angular measurements, velocities, temperatures, pressures and densities, and more.
Click here to learn more. You should bookmark this one.

Mike Likes: TI doubles power density with motor control

Texas Instruments recently introduced two new device families that help reduce size and weight in motor drive applications. When used together, the brushless DC (BLDC) gate drivers and power blocks require half the board space of competing solutions. An 18-V compact BLDC motor reference design demonstrates how these components can drive 11 W/cm³ power and enable engineers to jump start their designs for smaller, lighter weight power tools, integrated motor modules, drones, and more.
Read the full article.

Cool Tools: Laser scanner for reverse engineering

The new FARO Laser Tracker Vantage product family sets a new price/ performance standard for addressing challenges in large-scale metrology such as assembly alignment, part and assembly inspection, machine installation and alignment, and reverse engineering. Two high-performance Vantage models are available: E model (operating range to 25 m) and S model (operating range to 80 m). Both compact units offer industry-leading portability with an integrated master control unit (MCU), hot swappable batteries that eliminate the need for AC power and cabling, and industrial-grade Wi-Fi. A single carrying case makes for easy transport.
Click here to learn more.

Specifying intrinsically safe remote monitoring sensor systems for hazardous environments

Josh Schadel from SignalFire Telemetry lays out the plan for how to specify remote monitoring sensor systems for hazardous environs such as a tank- or well-level monitoring application that involves the storage of dangerous or volatile materials. Intrinsically safe (IS) equipment is designed so that energy levels are low enough not to generate an arc, spark, or temperature that could ignite an explosive area. IS equipment differs from explosion-proof (XP) systems where ignition is contained within an enclosure so as not to ignite the explosive environment.
Read Schadel's informative blog post.

Passive component design kit for IoT

The new Passive Components for the Internet of Things Design Kit (Part No. KIT-IOT) from AVX allows engineers to quickly identify effective solutions for IoT devices with widely varying requirements for power, data-processing speed, form factor, and price. The kit contains RF microwave components (capacitors, inductors, circuit protection, and SAW filters), input voltage filtering and decoupling devices, and high-precision crystal products to address a wide span of IoT applications including: wearable devices, smart-home applications, medical electronics, industrial automation tasks, connected cars, and traffic control.
Click here to learn more.

Cool Tools: New Fluke motor diagnostics tool incorporates machine learning

Fluke and Veros Systems have collaborated on asset performance and condition monitoring technologies to increase visibility into the efficiency and reliability of electric motor-driven machines. The Fluke 438-II Power Quality and Motor Analyzer is the first tool to result from that partnership. It analyzes three-phase power-quality measurements and uses an innovative method developed by Veros to calculate motor output torque, speed, horsepower, and efficiency. Using this information, engineers and technicians can evaluate system performance and detect overload conditions while the motor is operational, without the use of any mechanical sensing devices such as tachometers, strain gauges, or other intrusive sensors.
Click here to learn more.

New system can automatically retouch cellphone images and display result in real time -- before you take the photo

By Larry Hardesty, MIT

The data captured by today's digital cameras is often treated as the raw material of a final image. Before uploading pictures to social networking sites, even casual cellphone photographers might spend a minute or two balancing color and tuning contrast using one of the many popular image-processing programs now available.

Last week at Siggraph, the premier digital graphics conference, researchers from MIT's Computer Science and Artificial Intelligence Laboratory and Google presented a new system that can automatically retouch images in the style of a professional photographer. It's so energy efficient, however, that it can run on a cellphone, and it's so fast that it can display retouched images in real time, so that the photographer can see the final version of the image while still framing the shot.

The same system can also speed up existing image-processing algorithms. In tests involving a new Google algorithm for producing high-dynamic-range images, which capture subtleties of color lost in standard digital images, the new system produced results that were visually indistinguishable from those of the algorithm in about one-tenth the time -- again, fast enough for real-time display.

A new system can automatically retouch images in the style of a professional photographer. It can run on a cellphone and display retouched images in real time. [Courtesy of the researchers: Edited by MIT News]

 

 

 

 

The system is a machine-learning system, meaning that it learns to perform tasks by analyzing training data; in this case, for each new task it learned, it was trained on thousands of pairs of images, raw and retouched.

The work builds on an earlier project from the MIT researchers, in which a cellphone would send a low-resolution version of an image to a web server. The server would send back a "transform recipe" that could be used to retouch the high-resolution version of the image on the phone, reducing bandwidth consumption.

"Google heard about the work I'd done on the transform recipe," says Michaël Gharbi, an MIT graduate student in electrical engineering and computer science and first author on both papers. "They themselves did a follow-up on that, so we met and merged the two approaches. The idea was to do everything we were doing before but, instead of having to process everything on the cloud, to learn it. And the first goal of learning it was to speed it up."

VIDEO: Deep bilateral learning for real-time image enhancement.

Short cuts
In the new work, the bulk of the image processing is performed on a low-resolution image, which drastically reduces time and energy consumption. But this introduces a new difficulty, because the color values of the individual pixels in the high-res image have to be inferred from the much coarser output of the machine-learning system.

In the past, researchers have attempted to use machine learning to learn how to "upsample" a low-res image, or increase its resolution by guessing the values of the omitted pixels. During training, the input to the system is a low-res image, and the output is a high-res image. But this doesn't work well in practice; the low-res image just leaves out too much data.

Gharbi and his colleagues -- MIT professor of electrical engineering and computer science Frédo Durand and Jiawen Chen, Jon Barron, and Sam Hasinoff of Google -- address this problem with two clever tricks. The first is that the output of their machine-learning system is not an image; rather, it's a set of simple formulae for modifying the colors of image pixels. During training, the performance of the system is judged according to how well the output formulae, when applied to the original image, approximate the retouched version.

Taking bearings
The second trick is a technique for determining how to apply those formulae to individual pixels in the high-res image. The output of the researchers' system is a three-dimensional grid, 16 x 16 x 8. The 16 x 16 faces of the grid correspond to pixel locations in the source image; the eight layers stacked on top of them correspond to different pixel intensities. Each cell of the grid contains formulae that determine modifications of the color values of the source images.

That means that each cell of one of the grid's 16 x 16 faces has to stand in for thousands of pixels in the high-res image. But suppose that each set of formulae corresponds to a single location at the center of its cell. Then any given high-res pixel falls within a square defined by four sets of formulae.

Roughly speaking, the modification of that pixel's color value is a combination of the formulae at the square's corners, weighted according to distance. A similar weighting occurs in the third dimension of the grid, the one corresponding to pixel intensity.

The researchers trained their system on a data set created by Durand's group and Adobe Systems, the creators of Photoshop. The data set includes 5,000 images, each retouched by five different photographers. They also trained their system on thousands of pairs of images produced by the application of particular image-processing algorithms, such as the one for creating high-dynamic-range (HDR) images. The software for performing each modification takes up about as much space in memory as a single digital photo, so in principle, a cellphone could be equipped to process images in a range of styles.

Finally, the researchers compared their system's performance to that of a machine-learning system that processed images at full resolution rather than low resolution. During processing, the full-res version needed about 12 gigabytes of memory to execute its operations; the researchers' version needed about 100 megabytes, or one-hundredth as much. The full-resolution version of the HDR system took about 10 times as long to produce an image as the original algorithm, or 100 times as long as the researchers' system.

"This technology has the potential to be very useful for real-time image enhancement on mobile platforms," says Barron. "Using machine learning for computational photography is an exciting prospect but is limited by the severe computational and power constraints of mobile phones. This paper may provide us with a way to sidestep these issues and produce new, compelling, real-time photographic experiences without draining your battery or giving you a laggy viewfinder experience."

Published August 2017

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