MicroStrain Introduces Watt-Link Wireless Energy Monitoring on a Cloud-Enabled Network

LORD MicroStrain Sensing Systems announced the release of Watt-Link™, a new wireless energy and power monitoring sensor node which simplifies distributed installations and synchronizes with SensorCloud™ remote condition monitoring solutions. Watt-Link streamlines discrete industrial power installations and provides remote energy monitoring and reporting via any web-connected device. Applications include energy management, building automation, metering, and equipment performance monitoring, verification, evaluation, and diagnostics.

Watt-Link operates on the MicroStrain® LXRS® wireless communication network to achieve the simplicity of wireless use with the reliability of a hardwired system. Devices synchronize bidirectional power, energy, and demand data with other LORD MicroStrain condition-based monitoring including wireless strain, vibration, and temperature.

SensorCloud, a cloud-based data aggregation, visualization, and analytics platform, allows Watt-Link users to receive real-time alerts and custom reports via email and SMS. Furthermore, MathEngine® analytics provide a platform for rapidly identifying consumption trends and tracking metrics to maximize machine and manufacturing process efficiency. Each Watt-Link supports three current transformers with customizable gains and offsets. Models include 208Vac, WYE, 400Vac WYE, 480Vac, WYE, 240Vac Delta, 400Vac, Delta, 480Vac, Delta, and 600Vac, Delta.

“Distributed power and energy data is powerful for optimizing usage,” said Chris Townsend, Manager Embedded Sensing. “Watt-Link is unique because it combines the simplicity of wireless systems with the ability to synchronize measurements with other inputs that influence power consumption. The LXRS lossless wireless communication enables data to be reliably aggregated in harsh operating environments. This off-the-shelf solution allows operators to monitor equipment at a fraction of the cost of traditional hardwired technologies for more effective power consumption research, industrial manufacturing efficiency, and long-term machine health monitoring.”