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MEASUREMENT AND INSTRUMENTATION

CbM development platform these sensors. These were discussed and compared against
The CN-0549 CbM development platform, shown in Figure 11, existing ISO 10816 vibration standards, further identifying the
brings together all the MEMS design considerations outlined difference in performance of MEMS sensors for CbM.
above to offer the highest performance MEMS accelerometer MEMS sensors were classified according to the most
for CbM that can be mounted to an asset with ease, while important specifications, such as noise, bandwidth, g-range
maintaining data sheet performance. The data acquisition board and more. Due to their wide bandwidth, ultra-low noise and high
provides a high speed, 24-bit resolution signal conditioning and g-range, the ADXL100x family of sensors are clearly the only
data acquisition hardware solution for use with IEPE piezo-electric sensors capable of competing with piezo-electric accelerometers
and MEMS accelerometers. Also provided is all the necessary and, having been extensively compared to the MEMS competition,
firmware and evaluation software to run this system out of the can be considered the only high performance MEMS sensors
box. available today for CbM and PdM applications. In the medium
The CbM development platform is targeted at enabling CbM performance category, which is where all other MEMS CbM
designers to collect large amounts of high quality vibration data in sensors reside, Analog Devices offers a wide range of triaxial,
order to understand their asset’s operating behavior. Once this is digital sensors like ADXL317, one of the lowest noise, wide
understood, faults can be seeded or simulated in order to develop bandwidth digital MEMS accelerometers capable of detecting
trending information to allow the machine-learning algorithms vibrations early and helping to keep assets and even factories
to identify and profile a potential fault. This fault data must be running. n
captured with the highest fidelity and streamed to a machine-
learning environment to develop models to better understand the For more information on CbM sensors to CbM solutions, please
asset’s behaviour. visit analog.com/CbM.
The CbM development platform enables streaming of high
performance IEPE vibration sensor data to a machine-learning References
environment, such as TensorFlow, out of the box. A multitude 1. “Motor Monitoring Market by Offering (Hardware, Software),
of IEPE piezo-electric sensors (note these will not require the Monitoring Process (Online, Portable), Deployment, Industry
mounting cube to attach to an asset) or the ADXL1002 IEPE (Oil and Gas, Power Generation, Metals and Mining, Water
solution, CN-0532, can be used with the CbM development and Wastewater, Automotive), and Region — Global Forecast
platform. The DAQ board, CN-0540, another reference design to 2023.” Research and Markets, February 2019.
providing the highest precision data acquisition signal chain 2. Chris Murphy. “Choosing the Most Suitable Predictive
for IEPE sensors, provides a full bandwidth data pipeline into Maintenance Sensor.” Analog Devices, Inc., June 2020.
the FPGA where the system can monitor the data profile of the 3. Pete Sopcik and Dara O’Sullivan. “How Sensor Performance
machine. Enables Condition-Based Monitoring Solutions.” Analog
An oscilloscope application, running on the FPGA, requiring Dialogue, Vol. 53, No. 2. June 2019.
only a connection to a monitor via HDMI , provides frequency 4. Mark Looney. “MEMS Vibration Sensing: Velocity to
®
spectrum information and allows users to quickly visualise their Acceleration.” Analog Devices, Inc., March 2017.
machine’s health or to stream data to the cloud over Ethernet. 5. Mark Looney. “MEMS Vibration Monitoring: From Acceleration
Python and MATLAB bindings enable designers to directly to Velocity.” Analog Devices, Inc., June 2017.
®
interface the machine-learning data into these popular tools. 6. William Watts. “Triaxial Vibration Spectral Data: An Important
Designers can then take their machine-learning data and start Ingredient for Proper Machine Diagnostics.” Azima, DLI, 2009.
creating algorithms for their equipment to improve maintenance 7. “Understanding the Role of Transverse Sensitivity in
strategies, as well as predict failures and potential factory Measurement Data Reliability.” Endevco.
downtimes.
About the author
Conclusion Chris Murphy is an applications engineer with the European
This article discussed the most important criteria to be considered Centralised Applications Centre, based in Dublin, Ireland. He
when using MEMS accelerometers in CbM systems. It was has worked for Analog Devices since 2012, providing design
shown that a small number of MEMS accelerometers can offer support on motor control and industrial automation products.
a viable alternative to piezo-electric accelerometers; however, He holds an M.Eng. in electronics by research and a B.Eng.
significant gaps in performance were highlighted amongst MEMS in computer engineering. He can be reached at christopher.
accelerometers, outlining the requirement for a classification of murphy@analog.com.

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