February 21, 2017 Volume 13 Issue 07

Electrical/Electronic News & Products

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Intro to reed switches, magnets, magnetic fields

This brief introductory video on the DigiKey site offers tips for engineers designing with reed switches. Dr. Stephen Day, Ph.D. from Coto Technology gives a solid overview on reed switches -- complete with real-world application examples -- and a detailed explanation of how they react to magnetic fields.
View the video.


Bi-color LEDs to light up your designs

Created with engineers and OEMs in mind, SpectraBright Series SMD RGB and Bi-Color LEDs from Visual Communi-cations Company (VCC) deliver efficiency, design flexibility, and control for devices in a range of industries, including mil-aero, automated guided vehicles, EV charging stations, industrial, telecom, IoT/smart home, and medical. These 50,000-hr bi-color and RGB options save money and space on the HMI, communicating two or three operating modes in a single component.
Learn more.


All about slip rings: How they work and their uses

Rotary Systems has put together a really nice basic primer on slip rings -- electrical collectors that carry a current from a stationary wire into a rotating device. Common uses are for power, proximity switches, strain gauges, video, and Ethernet signal transmission. This introduction also covers how to specify, assembly types, and interface requirements. Rotary Systems also manufactures rotary unions for fluid applications.
Read the overview.


Seifert thermoelectric coolers from AutomationDirect

Automation-Direct has added new high-quality and efficient stainless steel Seifert 340 BTU/H thermoelectric coolers with 120-V and 230-V power options. Thermoelectric coolers from Seifert use the Peltier Effect to create a temperature difference between the internal and ambient heat sinks, making internal air cooler while dissipating heat into the external environment. Fans assist the convective heat transfer from the heat sinks, which are optimized for maximum flow.
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EMI shielding honeycomb air vent panel design

Learn from the engineering experts at Parker how honeycomb air vent panels are used to help cool electronics with airflow while maintaining electromagnetic interference (EMI) shielding. Topics include: design features, cell size and thickness, platings and coatings, and a stacked design called OMNI CELL construction. These vents can be incorporated into enclosures where EMI radiation and susceptibility is a concern or where heat dissipation is necessary. Lots of good info.
Read the Parker blog.


What is 3D-MID? Molded parts with integrated electronics from HARTING

3D-MID (three-dimensional mechatronic integrated devices) technology combines electronic and mechanical functionalities into a single, 3D component. It replaces the traditional printed circuit board and opens up many new opportunities. It takes injection-molded parts and uses laser-direct structuring to etch areas of conductor structures, which are filled with a copper plating process to create very precise electronic circuits. HARTING, the technology's developer, says it's "Like a PCB, but 3D." Tons of possibilities.
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Loss-free conversion of 3D/CAD data

CT CoreTech-nologie has further developed its state-of-the-art CAD converter 3D_Evolution and is now introducing native interfaces for reading Solidedge and writing Nx and Solidworks files. It supports a wide range of formats such as Catia, Nx, Creo, Solidworks, Solidedge, Inventor, Step, and Jt, facilitating smooth interoperability between different systems and collaboration for engineers and designers in development environments with different CAD systems.
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Top 5 reasons for solder joint failure

Solder joint reliability is often a pain point in the design of an electronic system. According to Tyler Ferris at ANSYS, a wide variety of factors affect joint reliability, and any one of them can drastically reduce joint lifetime. Properly identifying and mitigating potential causes during the design and manufacturing process can prevent costly and difficult-to-solve problems later in a product lifecycle.
Read this informative ANSYS blog.


Advanced overtemp detection for EV battery packs

Littelfuse has introduced TTape, a ground-breaking over-temperature detection platform designed to transform the management of Li-ion battery systems. TTape helps vehicle systems monitor and manage premature cell aging effectively while reducing the risks associated with thermal runaway incidents. This solution is ideally suited for a wide range of applications, including automotive EV/HEVs, commercial vehicles, and energy storage systems.
Learn more.


Benchtop ionizer for hands-free static elimination

EXAIR's Varistat Benchtop Ionizer is the latest solution for neutralizing static on charged surfaces in industrial settings. Using ionizing technology, the Varistat provides a hands-free solution that requires no compressed air. Easily mounted on benchtops or machines, it is manually adjustable and perfect for processes needing comprehensive coverage such as part assembly, web cleaning, printing, and more.
Learn more.


LED light bars from AutomationDirect

Automation-Direct adds CCEA TRACK-ALPHA-PRO series LED light bars to expand their offering of industrial LED fixtures. Their rugged industrial-grade anodized aluminum construction makes TRACKALPHA-PRO ideal for use with medium to large-size industrial machine tools and for use in wet environments. These 120 VAC-rated, high-power LED lights provide intense, uniform lighting, with up to a 4,600-lumen output (100 lumens per watt). They come with a standard bracket mount that allows for angle adjustments. Optional TACLIP mounts (sold separately) provide for extra sturdy, vibration-resistant installations.
Learn more.


World's first metalens fisheye camera

2Pi Optics has begun commercial-ization of the first fisheye camera based on the company's proprietary metalens technology -- a breakthrough for electronics design engineers and product managers striving to miniaturize the tiny digital cameras used in advanced driver-assistance systems (ADAS), AR/VR, UAVs, robotics, and other industrial applications. This camera can operate at different wavelengths -- from visible, to near IR, to longer IR -- and is claimed to "outperform conventional refractive, wide-FOV optics in all areas: size, weight, performance, and cost."
Learn more.


Orbex offers two fiber optic rotary joint solutions

Orbex Group announces its 700 Series of fiber optic rotary joint (FORJ) assemblies, supporting either single or multi-mode operation ideal for high-speed digital transmission over long distances. Wavelengths available are 1,310 or 1,550 nm. Applications include marine cable reels, wind turbines, robotics, and high-def video transmission. Both options feature an outer diameter of 7 mm for installation in tight spaces. Construction includes a stainless steel housing.
Learn more.


Mini tunnel magneto-resistance effect sensors

Littelfuse has released its highly anticipated 54100 and 54140 mini Tunnel Magneto-Resistance (TMR) effect sensors, offering unmatched sensitivity and power efficiency. The key differentiator is their remarkable sensitivity and 100x improvement in power efficiency compared to Hall Effect sensors. They are well suited for applications in position and limit sensing, RPM measurement, brushless DC motor commutation, and more in various markets including appliances, home and building automation, and the industrial sectors.
Learn more.


Panasonic solar and EV components available from Newark

Newark has added Panasonic Industry's solar inverters and EV charging system components to their power portfolio. These best-in-class products help designers meet the growing global demand for sustainable and renewable energy mobility systems. Offerings include film capacitors, power inductors, anti-surge thick film chip resistors, graphite thermal interface materials, power relays, capacitors, and wireless modules.
Learn more.


Voice control everywhere: New low-power special-purpose chip could make speech recognition ubiquitous in electronics

Researchers at MIT's Microsystems Technology Laboratories have built a low-power chip specialized for automatic speech recognition. With power savings of 90 to 99 percent, it could make voice control practical for relatively simple electronic devices. [Image: Jose-Luis Olivares/MIT]

 

 

 

 

By Larry Hardesty, MIT

The butt of jokes as little as 10 years ago, automatic speech recognition is now on the verge of becoming people's chief means of interacting with their principal computing devices.

In anticipation of the age of voice-controlled electronics, MIT researchers have built a low-power chip specialized for automatic speech recognition. Whereas a cellphone running speech-recognition software might require about 1 watt of power, the new chip requires between 0.2 and 10 milliwatts, depending on the number of words it has to recognize.

In a real-world application, that probably translates to a power savings of 90 to 99 percent, which could make voice control practical for relatively simple electronic devices. That includes power-constrained devices that have to harvest energy from their environments or go months between battery charges. Such devices form the technological backbone of what's called the "internet of things," or IoT, which refers to the idea that vehicles, appliances, civil-engineering structures, manufacturing equipment, and even livestock will soon have sensors that report information directly to networked servers, aiding with maintenance and the coordination of tasks.

"Speech input will become a natural interface for many wearable applications and intelligent devices," says Anantha Chandrakasan, the Vannevar Bush Professor of Electrical Engineering and Computer Science at MIT, whose group developed the new chip. "The miniaturization of these devices will require a different interface than touch or keyboard. It will be critical to embed the speech functionality locally to save system energy consumption compared to performing this operation in the cloud."

"I don't think that we really developed this technology for a particular application," adds Michael Price, who led the design of the chip as an MIT graduate student in electrical engineering and computer science and now works for chipmaker Analog Devices. "We have tried to put the infrastructure in place to provide better tradeoffs to a system designer than they would have had with previous technology, whether it was software or hardware acceleration."

Price, Chandrakasan, and Jim Glass, a senior research scientist at MIT's Computer Science and Artificial Intelligence Laboratory, described the new chip in a paper Price presented recently at the International Solid-State Circuits Conference.

The sleeper wakes
Today, the best-performing speech recognizers are, like many other state-of-the-art artificial-intelligence systems, based on neural networks, virtual networks of simple information processors roughly modeled on the human brain. Much of the new chip's circuitry is concerned with implementing speech-recognition networks as efficiently as possible.

But even the most power-efficient speech recognition system would quickly drain a device's battery if it ran without interruption. So the chip also includes a simpler "voice activity detection" circuit that monitors ambient noise to determine whether it might be speech. If the answer is yes, the chip fires up the larger, more complex speech-recognition circuit.

In fact, for experimental purposes, the researchers' chip had three different voice-activity-detection circuits, with different degrees of complexity and, consequently, different power demands. Which circuit is most power efficient depends on context, but in tests simulating a wide range of conditions, the most complex of the three circuits led to the greatest power savings for the system as a whole. Even though it consumed almost three times as much power as the simplest circuit, it generated far fewer false positives; the simpler circuits often chewed through their energy savings by spuriously activating the rest of the chip.

A typical neural network consists of thousands of processing "nodes" capable of only simple computations but densely connected to each other. In the type of network commonly used for voice recognition, the nodes are arranged into layers. Voice data are fed into the bottom layer of the network, whose nodes process and pass them to the nodes of the next layer, whose nodes process and pass them to the next layer, and so on. The output of the top layer indicates the probability that the voice data represents a particular speech sound.

A voice-recognition network is too big to fit in a chip's onboard memory, which is a problem because going off-chip for data is much more energy intensive than retrieving it from local stores. So the MIT researchers' design concentrates on minimizing the amount of data that the chip has to retrieve from off-chip memory.

Bandwidth management
A node in the middle of a neural network might receive data from a dozen other nodes and transmit data to another dozen. Each of those two dozen connections has an associated "weight," a number that indicates how prominently data sent across it should factor into the receiving node's computations. The first step in minimizing the new chip's memory bandwidth is to compress the weights associated with each node. The data are decompressed only after they're brought on-chip.

The chip also exploits the fact that, with speech recognition, wave upon wave of data must pass through the network. The incoming audio signal is split up into 10-millisecond increments, each of which must be evaluated separately. The MIT researchers' chip brings in a single node of the neural network at a time, but it passes the data from 32 consecutive 10-millisecond increments through it.

If a node has a dozen outputs, then the 32 passes result in 384 output values, which the chip stores locally. Each of those must be coupled with 11 other values when fed to the next layer of nodes, and so on. So the chip ends up requiring a sizable onboard memory circuit for its intermediate computations. But it fetches only one compressed node from off-chip memory at a time, keeping its power requirements low.

"For the next generation of mobile and wearable devices, it is crucial to enable speech recognition at ultralow power consumption," says Marian Verhelst, a professor of microelectronics at the Catholic University of Leuven in Belgium. "This is because there is a clear trend toward smaller-form-factor devices, such as watches, earbuds, or glasses, requiring a user interface which can no longer rely on touch screen. Speech offers a very natural way to interface with such devices."

The research was funded through the Qmulus Project, a joint venture between MIT and Quanta Computer, and the chip was prototyped through the Taiwan Semiconductor Manufacturing Company's University Shuttle Program.

Published February 2017

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