IQm, detects equipment faults 6 months before unexpected failure occurs by using the patented and award-winning predictive maintenance technology of Artesis. Unlike other technologies, IQm is affordable and requires no expertise.
IQm generates a comprehensive condition report by analyzing the voltage and current data taken from the metering devices such as Fluke 435 – II and Fluke 437 – II energy analyzers.
Many users are aware of the connection between deteriorating condition and reduced efficiency. Excessive misalignment, voltage imbalance or mechanical unbalance can have serious impact, as can heating caused by bearing or electrical problems. The ability to proactively manage such problems allows condition monitoring to have a direct impact on operating efficiency.
Artesis solutions can be used to monitor
electric motor efficiency and to
maintain efficient motor operation.
Artesis, founded in 1999, developed a unique technology for early warning of pending failures of industrial equipment. This technology is used to increase productivity and energy efficiency by preventing unexpected downtime and faulty operation of equipment. This unique and patented technology received 40 Best Products Award by Control Engineering Magazine, USA, and the Innovation award by the Institution of Engineering and Technology, UK. GE Energy became a shareholder of Artesis in 2010.
Click here for more infoIQm monitors the condition of equipment driven by an electric motor, effectively using the motor itself as a sophisticated transducer. It uses advanced NASA-developed model-based-fault-detection technology to provide automated set-up and fault diagnosis with minimal user intervention. It is simpler to use and more cost effective than conventional systems. IQm is applicable to a very wide range of driven equipment, including pumps, fans, compressors, and conveyors, and is particularly valuable for equipment in inaccessible or hazardous environments.
Click here for more infoOur technology received “Editor’s Choice Award”, 40 Best Products of 2000, Control Engineering USA and “Technology Innovation Award 2007” for simplifying predictive maintenance, The Institution of Engineering,UK.
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