Nanoprecise Sci Corp > Case Studies > Automatic monitoring of acoustic emission saves catastrophic failure

Automatic monitoring of acoustic emission saves catastrophic failure

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 Automatic monitoring of acoustic emission saves catastrophic failure - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Edge Analytics
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Remote Monitoring & Control Systems
  • Sensors - Acoustic Sensors
  • Sensors - Humidity Sensors
  • Sensors - Temperature Sensors
Applicable Industries
  • Construction & Infrastructure
Applicable Functions
  • Discrete Manufacturing
Use Cases
  • Machine Condition Monitoring
The Challenge

Traditional measurement tools are ineffective when it comes to slowly rotating equipment. There are faults like Bearing Failure, Ring Plugging, Gear Tooth Crack and many more which can lead to the shutdown of machines. 1 minute of downtime cost the company $10. RingPluggingis a very common issue which Pinnacle Pellet was facing very frequently due to diverse feed quality into the machines. Product ring plugging can be detected as sound levels increase in specific roller bearings.

The Customer
Pinnacle Pellet
About The Customer
Pinnacle currentlyoperates 7 industrial wood pellet production facilities with a combined production capacity in excess of 1.4 million metric tons and are well-positioned to support this rapidly growing demand through the construction of new capacity.
The Solution

We proposed our RotationLF system under which we installed wireless sensors as a part of a pilot project on multiple types of equipment.

RotationLFhas several features including:

- Vibration, Acoustic Emission & Temperature, Humidity & RPM

- Online Diagnosis

- Fault detection

Once installed, strong battery-powered wireless sensors started monitoring pump and motors and sent data to our SaaS-based platform through an encrypted & secured network using Edge and Cloud computing. As data was received, RotationLF platform worked on data analysis using highly sophisticated algorithms.

Approximately 1 month after the sensors were installed, the system alerted Pinnacle that fault had been detected on the equipment named Pelletor 5 specifying the reason for notification sown in the image on right. The acoustic emission pattern depicted in the system is indicative of an early-stage failure.

Operational Impact
  • [Data Management - Data Availability]

    The RotationLF analytics sensed & detected the anomaly in the pattern and alerted Pinnacle plant staff about this unusual trend automatically through mobile text and email alert.

  • [Process Optimization - Predictive Maintenance]

    Formation of the roll failure was detected hours before the equipment was stopped for maintenance. This gave plant personnel valuable time to organize maintenance activities.

Quantitative Benefit
  • As per Pinnacle, 1 minute of shutdown can cost them up to $10. Notifying at a very early stage, plant personnel could decide to take preventive action to reduce the load and keep running the equipment for 6 hours which saved unplanned downtime cost.

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