The MAX78638 is a fully integrated solution containing a microcontroller, compute engine (with preloaded firmware), and a high-accuracy analog-to-digital converter (ADC). Its flexible and configurable sensor interfaces allow for the measurement of current, voltage, speed, vibration, position, and temperature. By monitoring up to 10 sensors and calculating the mean time to failure (MTTF) and energy consumption, a motor’s health can be assessed. The solution’s preloaded firmware shortens development time by giving the customers easy access to these sensor measurements. The high-accuracy ADC enables a less than 0.5% energy calculation error compared to the 5% of a standard microprocessor solution.
In process automation there are mission-critical pumps and motors that, if not operating correctly, can cause a factory to shut down. In processing plants such as paper mills and oil refineries, the cost of stopping operation could result in the loss of hundreds of thousands of dollars or more. Previously, the diagnostic solutions used to monitor these motors were large and expensive, including equipment such as infrared thermography, vibration analyzers, and precision power quality submeters.
Multiple MAX78638s can be placed on many different motors simultaneously to monitor long-time drift, track trends, and quickly detect faults. The solution is low cost and simple to use and can be used with rental motors or small motors that do not already have diagnostic capabilities built in or provided by a separate motor drive.
Preloaded firmware with documentation and source code help to reduce measurement development times.
Maxim Integrated plans to demonstrate the benefits of using the MAX78638 to measure and monitor the health of motors in an industrial application. The live demo will take place at electronica 2012 (Munich, Germany, November 13 to 16 in Hall A6, Booth 163.
The MAX78638 SoC will form the brains of health monitoring system designed to determine several motor failures before they happen. Participants at the demo will be able to determine several motor health indicators including detecting