RMWIS is a compact wireless vibration analysis sensor designed for portable machine condition monitoring and intelligent fault diagnosis. Using a smartphone app, it performs instant vibration measurements, analyzes acceleration, velocity, displacement, envelope, waveform, and spectrum data, while automatically detecting common machine faults such as bearing defects, imbalance, misalignment, and mechanical looseness. Its wireless operation enables maintenance teams to quickly inspect rotating equipment and store measurement data for future analysis and predictive maintenance. :contentReference[oaicite:0]{index=0}
RMWIS is a portable wireless vibration analysis sensor designed for instant machine condition monitoring. Using a smartphone app, it performs automatic vibration analysis, intelligent fault diagnosis, and comprehensive machine health assessment, making predictive maintenance faster, easier, and more efficient. :contentReference[oaicite:0]{index=0}
Perform complete vibration analysis directly from a mobile application.
Measure acceleration, velocity, displacement, envelope, waveform and spectrum.
Automatically identifies common machine faults and bearing conditions.
Capture vibration data without cables for fast and convenient inspections.
Supports scheduled inspections as well as instant on-demand measurements.
Save all measurement results for future comparison, trending and reporting.
Quickly inspect multiple rotating machines throughout your facility.
Detect imbalance, misalignment, bearing failures and mechanical defects before breakdowns.
RMWIS (Remote Machine Wireless Inspection System) is a portable wireless vibration analysis solution developed for rapid machine condition assessment and predictive maintenance. Using a compact wireless sensor and smartphone application, RMWIS measures acceleration, velocity, displacement, envelope, waveform and FFT spectrum to quickly evaluate machine health and identify developing faults before unexpected failures occur.
Designed for maintenance engineers and reliability professionals, RMWIS features wireless Bluetooth communication, AI-assisted fault diagnosis, route-based inspections, cloud-ready data management, and comprehensive vibration reporting. It enables fast machine inspections, historical trend analysis, bearing diagnostics, and predictive maintenance while reducing downtime and improving overall equipment reliability.
RMWIS is developed for portable vibration analysis and machine condition monitoring across industrial facilities. It enables maintenance engineers to perform fast inspections, diagnose machine faults, and support predictive maintenance using wireless data acquisition and AI-assisted vibration analysis.
Inspect motors, pumps, fans, gearboxes and compressors during routine maintenance.
Evaluate generators, turbines and auxiliary equipment for early fault detection.
Analyze pumps, compressors and process machinery using wireless vibration measurements.
Monitor mills, crushers, conveyors and heavy rotating equipment.
Perform vibration inspections on pumps, motors and treatment equipment.
Ideal for reliability engineers performing route-based machine inspections.
Collect vibration data wirelessly using a compact portable sensor.
Measure acceleration, velocity, displacement, envelope, waveform and FFT spectrum.
Automatically identify bearing, imbalance, misalignment and gearbox faults.
Perform inspections directly from a smartphone with an intuitive interface.
Create inspection routes for efficient machine condition assessments.
Track machine health over time to identify developing faults early.
Store inspection data securely and generate professional maintenance reports.
Lightweight and rugged system built for everyday industrial field inspections.
Make machine inspections faster, smarter, and more reliable with the RMWIS (Remote Machine Wireless Inspection System). Featuring wireless vibration measurement, AI-assisted fault diagnosis, real-time machine health analysis, and intuitive mobile reporting, RMWIS helps maintenance teams detect faults early, reduce unplanned downtime, improve equipment reliability, and optimize predictive maintenance across industrial operations.
