The enervisual sensor range — order-based spectra, raw time waveforms, and a 10-year battery life in one wireless package.
For decades, vibration monitoring has forced a choice.
Either you install a wired system — analyst-grade data quality, but cabling, cabinets, mains power, and an installation project that makes sense only for your most critical machines. Or you deploy simple wireless pucks — easy to mount, but delivering little more than overall RMS values that tell you something changed without telling you what.
The result is predictable: a small number of machines get properly monitored, and everything else runs blind. The gearbox in a remote wind turbine. The gear motors driving a production line. The pumps, fans, and agitators that keep a process plant running. Machines that matter — but never mattered enough to justify pulling cable.
The enervisual sensor range removes that choice. Full analyst-grade vibration data, delivered wirelessly, from a battery that lasts up to 10 years.
Measurement Quality First
Wireless monitoring has a reputation problem, and it is earned: too many wireless products sample too slowly, resolve too coarsely, and compress the signal until only a trend indicator survives.
We built the enervisual nodes to the standard a vibration analyst expects:
- Sampling up to 16 kHz — capturing bearing defect frequencies and gear mesh harmonics well into the range where early faults appear
- Ultralow noise floor — in the 20–27 µg/√Hz class — early-stage faults produce microscopic vibration amplitudes; detecting them is a signal-to-noise battle, and it is won or lost in the sensor itself. This noise performance is what makes the difference between seeing a bearing defect in its first weeks and seeing it six months later
- 20-bit resolution — the dynamic range to see a small developing defect next to dominant machine vibration
- Raw time waveform (TWF) capture — not just processed indicators, but the actual signal, available for download and independent analysis
- IP67-rated housings with an industrial temperature range, mounted by stud or magnet in minutes
The raw waveform matters more than any specification sheet. It means the data can be verified, re-analyzed, and trusted. When our platform flags a bearing fault, your analyst — or ours — can open the underlying TWF and confirm it. Nothing is hidden inside a proprietary index.
Order-Based Analysis: Built for Machines That Change Speed
Most real machines do not run at one fixed speed. Wind turbine drivetrains follow the wind. Process drives follow production demand. Motors on variable frequency drives follow their setpoint.
For a conventional frequency spectrum, that is a problem: as shaft speed drifts during a measurement, every speed-related peak — gear mesh, bearing defects, imbalance — smears across neighboring frequencies. Faults blur into the noise floor precisely when you need them sharp.
Order-based analysis solves this. By normalizing the spectrum to shaft rotation, every component signature stays locked in place regardless of operating speed: the gear mesh is always at its tooth-count order, the bearing defect always at its characteristic order. A fault trend built on orders is comparable across measurements taken at different speeds — which, on a variable-speed machine, is every measurement.
This is a capability that separates monitoring systems from data loggers. The enervisual nodes deliver both conventional spectra and order-normalized spectra, with the speed reference handled as part of the system design.
Measurements can also be scheduled against operating conditions — capturing data when the machine is in a defined, comparable state rather than at random moments. This does double duty: it makes trends meaningful, and it is one of the reasons the battery lasts as long as it does. Intelligent measurement scheduling, not continuous streaming, is how you get a decade of monitoring from a battery.
A Complete System, Not a Component List
A vibration sensor on its own monitors nothing. The data has to travel, land somewhere, and become an answer.
The enervisual package includes the whole chain:
- Wireless data transmission from node to gateway to cloud — long-range, low-power, built for industrial sites and remote structures alike
- Web-based analysis tools — trends, spectra, waterfall plots, TWF download, alarm management — accessible from any browser, no software installation, no per-seat analysis licenses
- Integration APIs — your vibration data delivered into your existing systems: maintenance platforms, historians, dashboards, or your own analytics
That last point reflects a principle: your data stays yours. The API works in both directions — our platform can feed your systems, and it can ingest data from monitoring hardware you already own. No lock-in, in either direction. For anyone who has been trapped in a proprietary monitoring ecosystem, this is not a footnote.
Commercially, it means the price you see is the price of a working monitoring system — not a sensor that later needs a gateway, which later needs a software license, which later needs an analysis module.
From Data to Diagnosis
Hardware and infrastructure get the data out of the machine. Turning it into a maintenance decision is the final step — and the one where most monitoring initiatives stall.
This is where the enervisual platform’s pre-configured spectral libraries and AI-supported diagnostics take over. For supported machine types, the system already knows which orders belong to which components — every gear mesh, every bearing — and identifies developing faults at the component level: not “vibration increased,” but which bearing, which stage, how severe, and since when.
We have written about how that works in detail: Your Turbine Type. Our Spectral Data. Ready to Go.
One Sensor Range, Many Industries
The engineering problem is the same everywhere: rotating machinery, developing faults, and the cost of finding out too late.
We built our first deployments on wind turbines — among the most demanding environments for wireless monitoring, with variable speeds, remote locations, and structures where cabling is prohibitively invasive. Today the same nodes monitor drivetrains and process equipment beyond wind: production lines, drives, pumps, and rotating equipment in the food and process industries, where hygiene zones, washdown areas, and flexible production layouts make cabled systems just as impractical as a turbine nacelle.
More on that soon.
The Short Version
- Analyst-grade data: up to 16 kHz sampling, 20-bit resolution, 20–27 µg/√Hz noise floor, raw TWF
- Order-based spectra built for variable-speed machines
- Up to 10 years of battery life through intelligent measurement scheduling
- Wireless transmission, web analysis tools, and integration APIs included
- No cabling, no machine downtime for installation, no vendor lock-in
If there is rotating machinery in your operation that has never justified a wired monitoring project — that justification problem is gone.
Contact the enervisual team to discuss your machines.
Learn more about enervisual’s battery-wireless monitoring solutions at enervisual.com
0 Comments