Online electric monitoring system

Paul Boughton
SKF, the leading knowledge engineering company, and Baker Instrument Company, a specialist electric motor management company, have joined forces to launch a new online motor analysis system to enable ongoing automated evaluation of critical electric motor assets, significantly reducing the cost of ownership.

Called the NetEP, this networked system has been designed to allow data analysis to be accessed globally at any time via the internet, providing vital data for industries where critical electric motor assets are operated over extended or continuous periods and are only shut down during planned outages, such as in the power generation and utilities sectors.
Offering reliable and consistent monitoring between planned outages, the new NetEP system has been developed to identify weakening or faulty rotating equipment that can lead to motor failure, potentially costly and unexpected downtime, and production losses. Perhaps most importantly, this online analysis system warns users of critical situations with an easy to read interface, maintaining all database functionality, as well as providing enhanced data trend analysis. In doing so, the NetEP makes a positive contribution towards overall plant safety, particularly in view of the risks associated with live electrical networks.
In addition, the new system eliminates the need for route-based monitoring with portable devices, as data can be collected from 32 motors at the same time, on more than 140 parameters, with results that can be accessed from any location with an internet connection.
Curt Lanham, President of Baker Instrument Company, said: “We are extremely excited to announce the launch of this new online system, which is a natural evolution in our electric motor testing portfolio. It takes the proven capabilities of our market leading EXP technology, adding 24/7 monitoring with multiple user defined parameters.”
“By increasing the frequency of monitoring, we improve our knowledge of a motor’s health, allowing us to identify early signs of concern and to spot any deterioration patterns through data trends. As a result we can help our customers achieve significant maintenance and operational related cost savings. In addition, the system can aid in cost and energy savings through better understanding of a motor’s efficiency and performance in a given application, helping achieve better energy savings.”

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