Analog Devices uses sensor data to monitor development
A condition-based monitoring development platform from Analog Devices supports engineers by helping to accelerate condition monitoring hardware, software and algorithm development.
The CN0549 condition-based monitoring development platform provides mechanically secure, wide bandwidth sensor data with robust, high fidelity data acquisition, says the company. It has open source software interfaces to simplify connectivity from embedded systems to popular data analysis tools, such as MATLAB and Python. CN0549 enables real-time vibration data processing to accelerate the development of machine learning algorithms which can be used for predictive maintenance services. Engineers can use the platform to accelerate condition monitoring developments and significantly reduce development costs and risk, claims Analog Devices.
In particular, the CN0549 reference design has a wide-bandwidth (DC to 10kHz) MEMS vibration sensor, which is compatible with existing piezoelectric IEPE compliant interfaces.
There is also a mechanical mounting cube which enables full-bandwidth mechanical transfer function of the MEMs vibration sensor. A wide bandwidth, high fidelity data acquisition system reference design is available for IEPE-compatible sensors.
The embedded gateway uses industry standard open source software for data processing. In addition, the platform streams vibration data into popular machine learning environments such as MATLAB, TensorFlow, and other Python based tools for algorithm development using step-by-step examples.
The EVAL-CN0532-EBZ, IEPE-compatible interface for wideband MEMS accelerometer sensor, the EVAL-XLMOUNT1, mechanically optimised mounting block for MEMs accelerometer boards, the EVAL-CN0540-ARDZ 24-bit data acquisition system for IEPE sensors and the DE10-Nano or Cora Z7-07s FPGA development boards are all in production now. The FPGA boards are available through Analog Device distributors.
