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Overhung load adaptors provide load support and contamination protection

Overhung load adaptors (OHLA) provide both overhung radial and axial load support to protect electrified mobile equipment motors from heavy application loads, extending the lifetime of the motor and alleviating the cost of downtime both from maintenance costs and loss of production. They seal out dirt, grime, and other contaminants too. Zero-Max OHLAs are available in an extensive offering of standard models (including Extra-Duty options) for typical applications or customized designs.
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Why choose electric for linear actuators?

Tolomatic has been delivering a new type of linear motion technology that is giving hydraulics a run for its money. Learn the benefits of electric linear motion systems, the iceberg principle showing total cost of ownership, critical parameters of sizing, and conversion tips.
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New AC hypoid inverter-duty gearmotors

Bodine Electric Company introduces 12 new AC inverter-duty hypoid hollow shaft gearmotors. These type 42R-25H2 and 42R-30H3 drives combine an all-new AC inverter-duty, 230/460-VAC motor with two hypoid gearheads. When used with an AC inverter (VFD) control, these units deliver maintenance-free and reliable high-torque output. They are ideal for conveyors, gates, packaging, and other industrial automation equipment that demands both high torque and low power consumption from the driving gearmotor.
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Next-gen warehouse automation: Siemens, Universal Robots, and Zivid partner up

Universal Robots, Siemens, and Zivid have created a new solution combining UR's cobot arms with Siemens' SIMATIC Robot Pick AI software and Zivid's 3D sensors to create a deep-learning picking solution for warehouse automation and intra-logistics fulfillment. It works regardless of object shape, size, opacity, or transparency and is a significant leap in solving the complex challenges faced by the logistics and e-commerce sectors.
Read the full article.

Innovative DuoDrive gear and motor unit is UL/CSA certified

The DuoDrive integrated gear unit and motor from NORD DRIVE-SYSTEMS is a compact, high-efficiency solution engineered for users in the fields of intralogistics, pharmaceutical, and the food and beverage industries. This drive combines a IE5+ synchronous motor and single-stage helical gear unit into one compact housing with a smooth, easy-to-clean surface. It has a system efficiency up to 92% and is available in two case sizes with a power range of 0.5 to 4.0 hp.
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BLDC flat motor with high output torque and speed reduction

Portescap's 60ECF brushless DC slotted flat motor is the newest frame size to join its flat motor portfolio. This 60-mm BLDC motor features a 38.2-mm body length and an outer-rotor slotted configuration with an open-body design, allowing it to deliver improved heat management in a compact package. Combined with Portescap gearheads, it delivers extremely high output torque and speed reduction. Available in both sensored and sensorless options. A great choice for applications such as electric grippers and exoskeletons, eVTOLs, and surgical robots.
Learn more and view all the specs.

Application story: Complete gearbox and coupling assembly for actuator system

Learn how GAM engineers not only sized and selected the appropriate gear reducers and couplings required to drive two ball screws in unison using a single motor, but how they also designed the mounting adapters necessary to complete the system. One-stop shopping eliminated unnecessary components and resulted in a 15% reduction in system cost.
Read this informative GAM blog.

Next-gen motor for pump and fan applications

The next evolution of the award-winning Aircore EC motor from Infinitum is a high-efficiency system designed to power commercial and industrial applications such as HVAC fans, pumps, and data centers with less energy consumption, reduced emissions, and reduced waste. It features an integrated variable frequency drive and delivers upward of 93% system efficiency, as well as class-leading power and torque density in a low-footprint package that is 20% lighter than the previous version. Four sizes available.
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Telescoping linear actuators for space-constrained applications

Rollon's new TLS telescoping linear actuators enable long stroke lengths with minimal closed lengths, which is especially good for applications with minimal vertical clearance. These actuators integrate seamlessly into multi-axis systems and are available in two- or three-stage versions. Equipped with a built-in automated lubrication system, the TLS Series features a synchronized drive system, requiring only a single motor to achieve motion. Four sizes (100, 230, 280, and 360) with up to 3,000-mm stroke length.
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Competitively priced long-stroke parallel gripper

The DHPL from Festo is a new generation of pneumatic long-stroke grippers that offers a host of advantages for high-load and high-torque applications. It is interchangeable with competitive long-stroke grippers and provides the added benefits of lighter weight, higher precision, and no maintenance. It is ideal for gripping larger items, including stacking boxes, gripping shaped parts, and keeping bags open. It has high repetition accuracy due to three rugged guide rods and a rack-and-pinion design.
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Extend your range of motion: Controllers for mini motors

FAULHABER has added another extremely compact Motion Controller without housing to its product range. The new MC3603 controller is ideal for integration in equipment manufacturing and medical tech applications. With 36 V and 3 A (peak current 9 A), it covers the power range up to 100 W and is suitable for DC motors with encoder, brushless drives, or linear motors.
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When is a frameless brushless DC motor the right choice?

Frameless BLDC motors fit easily into small, compact machines that require high precision, high torque, and high efficiency, such as robotic applications where a mix of low weight and inertia is critical. Learn from the experts at SDP/SI how these motors can replace heavier, less efficient hydraulic components by decreasing operating and maintenance costs. These motors are also more environmentally friendly than others.
View the video.

Tiny and smart: Step motor with closed-loop control

Nanotec's new PD1-C step motor features an integrated controller and absolute encoder with closed-loop control. With a flange size of merely 28 mm (NEMA 11), this compact motor reaches a max holding torque of 18 Ncm and a peak current of 3 A. Three motor versions are available: IP20 protection, IP65 protection, and a motor with open housing that can be modified with custom connectors. Ideal for applications with space constraints, effectively reducing both wiring complexity and installation costs.
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Closed loop steppers drive new motion control applications

According to the motion experts at Performance Motion Devices, when it comes to step motors, the drive technique called closed loop stepper is making everything old new again and driving a burst of interest in the use of two-phase step motors. It's "winning back machine designers who may have relegated step motors to the category of low cost but low performance."
Read this informative Performance Motion Devices article.

Intelligent compact drives with extended fieldbus options

The intelligent PD6 compact drives from Nanotec are now available with Profinet and EtherNet/IP. They combine motor, controller, and encoder in a space-saving package. With its 80-mm flange and a rated power of 942 W, the PD6-EB is the most powerful brushless DC motor of this product family. The stepper motor version has an 86-mm flange (NEMA 34) and a holding torque up to 10 Nm. Features include acceleration feed forward and jerk-limited ramps. Reduced installation time and wiring make the PD6 series a highly profitable choice for machine tools, packaging machines, or conveyor belts.
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Scary! SwRI engineers come up with ways to trick vehicle object detection systems

Many of today's vehicles use object detection systems to help avoid collisions. SwRI engineers developed unique patterns that can trick these systems. In this photo, the object detection system sees a person rather than a vehicle. This research will allow engineers to thoroughly test object detection systems and improve the security of the deep-learning algorithms they use. [Credit: Southwest Research Institute]

 

 

 

 

New adversarial techniques developed by engineers at Southwest Research Institute can make objects "invisible" to image detection systems that use deep-learning algorithms. These techniques can also trick systems into thinking they see another object or can change the location of objects. The technique mitigates the risk for compromise in automated image-processing systems.

"Deep-learning neural networks are highly effective at many tasks," says Research Engineer Abe Garza of the SwRI Intelligent Systems Division. "However, deep learning was adopted so quickly that the security implications of these algorithms weren't fully considered."

Deep-learning algorithms excel at using shapes and color to recognize the differences between humans and animals or cars and trucks, for example. These systems reliably detect objects under an array of conditions and, as such, are used in myriad applications and industries, often for safety-critical uses. The automotive industry uses deep-learning object detection systems on roadways for lane-assist, lane-departure and collision-avoidance technologies. These vehicles rely on cameras to detect potentially hazardous objects around them. While the image processing systems are vital for protecting lives and property, the algorithms can be deceived by parties intent on causing harm.

Security researchers working in "adversarial learning" are finding and documenting vulnerabilities in deep- and other machine-learning algorithms. Using SwRI internal research funds, Garza and Senior Research Engineer David Chambers developed what look like futuristic, Bohemian-style patterns. When worn by a person or mounted on a vehicle, the patterns trick object detection cameras into thinking the objects aren't there, that they're something else or that they're in another location. Malicious parties could place these patterns near roadways, potentially creating chaos for vehicles equipped with object detectors.

"These patterns cause the algorithms in the camera to either misclassify or mislocate objects, creating a vulnerability," said Garza. "We call these patterns 'perception invariant' adversarial examples because they don't need to cover the entire object or be parallel to the camera to trick the algorithm. The algorithms can misclassify the object as long as they sense some part of the pattern."

What looks like a colorful pattern to the human eye looks like a bicycle to an object detection system. While deep-learning algorithms used in these systems are reliable, they can be deceived with special imagery. SwRI researchers are developing techniques to mitigate the risk of compromise in these systems. [Credit: Southwest Research Institute]

 

 

 

 

While they might look like unique and colorful displays of art to the human eye, these patterns are designed in such a way that object-detection camera systems see them very specifically. A pattern disguised as an advertisement on the back of a stopped bus could make a collision-avoidance system think it sees a harmless shopping bag instead of the bus. If the vehicle's camera fails to detect the true object, it could continue moving forward and hit the bus, causing a potentially serious collision.

"The first step to resolving these exploits is to test the deep-learning algorithms," said Garza. The team has created a framework capable of repeatedly testing these attacks against a variety of deep-learning detection programs, which will be extremely useful for testing solutions.

VIDEO: Adversarial Learning: SwRI engineers developed unique patterns that can trick these systems into seeing something else, seeing the objects in another location, or not seeing the objects at all.

SwRI researchers continue to evaluate how much, or how little, of the pattern is needed to misclassify or mislocate an object. Working with clients, this research will allow the team to test object detection systems and ultimately improve the security of deep-learning algorithms.

Source: SwRI

Published April 2019

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