Move on this: Smart vibration analysis

Sheila Kennedy says better monitoring tools allow for greater flexibility, more-precise diagnostics.

By Sheila Kennedy, CMRP, contributing editor

Vibration is a tried-and-true indicator of equipment health. Developments spawned from the internet of things (IoT) are making vibration data monitoring and analysis easier and more widely applicable. Targeted solutions and complete ecosystems allow companies to avoid reactive maintenance and unplanned downtime resulting from imbalance, misalignment, bearing faults, and similar concerns.

New answers to common challenges


A new approach to vibration analysis uses high-definition digital enveloping, extracting, and enhancing of signals buried in machine noise. The HD ENV from SPM Instrument leverages this technology to allow customers to take control of assets that were previously not measurable due to low RPM speeds.

“Typically, vibration analysis technology has been very conservative – the last patent with a technology breakthrough in our industry is over 20 years old,” says Ron Kittle, managing director at SPM Instrument. “HD technologies provide never-before-seen crisp and sharp results that give very early indications of bearing and gear damage. Increased prewarning times on critical machines is the largest benefit, even in the most challenging or low-speed applications.”

Machine Dossier from SEC-America is a reliability ecosystem that resides in the cloud and collects vibration data wirelessly. Its original ZARK general-purpose sensing device is joined by the new X8, which separates the sensors from the rest of the device to enable monitoring of high-temperature equipment. It can be used with any off-the-shelf vibration sensing device and serves a wider range of applications.

“We learned in the industry that one-size-fits-all wireless vibration technology does not fit all applications,” says Will Tudoroff, product manager at SEC-America. “The problem with self-contained wireless designs is that the battery can only handle a certain temperature range. We separated the sensors so they can be mounted directly on high-temperature equipment while the battery part is a few feet away from the heat source.”

Component Analyzer from MachineSense is a fully edge-enabled vibration analyzer that tracks the trend health and operating conditions of rotating industrial machinery components. The compact, multisensing system identifies abnormal vibration, machine utilization, ambient operating conditions, bearing health, and sensor installation. Analytic data is accessible through a web browser or mobile app.

The analyzer’s extremely lightweight, metal powder-filled polymer housing enables quick and easy magnetic mounting on a machine’s surface, says James Zinski, CEO of MachineSense. “Any improper installation or loose mounting is detected though analytics and sent as an alarm to users,” he adds.

Traditionally, eddy current sensor measurement chains for vibration monitoring required a choice between carrying expensive quantities of spare parts and sensors and risking production downtime while waiting for factory-calibrated replacements, says Drew Mackley, reliability solutions director for Emerson.

“Now, instead of needing multiple converters calibrated to specific sensor chains, a single converter – the AMS EZ 1000 digital converter – can calibrate all eddy current sensor chains in the field,” Mackley says. “The result is producers can carry fewer spares and not risk production downtime waiting for factory calibration,” he explains. The converter is compatible with third-party sensors and is API 670-compliant.

Holistic predictive ecosystems


Integrating all machine condition data allows for more-coordinated analytics and asset management. Intel provides building blocks for condition monitoring and analytics. Products from Intel and its IoT Solutions Alliance partners form an ecosystem that supports sensor data acquisition and analytics in addition to other Industry 4.0 initiatives. Intel IoT Gateways, for example, enables connectivity of legacy industrial devices and systems to the IoT.

“A critical factor for our customers is transparency in operations and improving yields and uptime,” says Irene Petrick, director of industrial innovation for Intel’s Industrial Solutions Division. “Putting sensors in the right place to get the right data (which is not always the obvious data) is a critical element of that.”

SKF USA has been working to create “an environment for excellent rotating equipment performance” by integrating monitoring tools and techniques with deep understanding of bearing systems, modeling, and failure analysis.

“This is honestly a very exciting time in predictive maintenance as we begin to merge the old way with the new,” says John Cardwell, applications engineer at SKF USA. “Our recent advancements in connectivity, equipment form factor, and automation are helping realize an industrial environment where we can focus our efforts on innovation, productivity, and reduced environmental impact as less time is spent reacting to unexpected failures, collecting manual data, and ordering parts.”

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