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  1. Real-time maintenance
  2. Vibration
  3. Product platforms
  4. IO-Link vibration monitoring

IO-Link vibration monitoring

Simple to implement industrial-grade machine vibration condition monitoring

  • Easily protect your machinery from damaging conditions.
  • Automate your machine condition monitoring with real-time indicators of impact, fatigue, friction, and temperature.
  • Seamless integration directly into Industrial Ethernet systems via IO-Link.
  • No control cabinets or extensive wiring required for installation.
  • Leverage your existing control network for process and Real-time Maintenance.

Industrial-grade machine protection integrates directly into your existing control platform. Machine condition is continually monitored for common fault conditions of impacts, component fatique, and friction. This allows timely and predictable scheduling of maintenance before major damage or failure and production downtime. Machines are continuously and permanently protected, unlike when using intermittent single measurement monitoring systems.

  • Simple installation
  • Accurate equipment condition assessment
  • Automated alerts
  • Root cause analysis tools without the complexity and high price

Measurements

The VV design aims to simplify the primary categories of machine failure. Unlike typical single measurement systems, the VV simultaneously monitors equipment for the four categories of machine problems: impact, fatigue, friction, and temperature. The embedded IO-Link technology provides this data in real time, giving the VV sensor the capability to predict pending failures and mitigate catastrophic damage.

 
Example fault
conditions

Blades hitting
Ingested object
Struck by moving object
Improper sequence timing

Misalignment
Unbalance
Belt issues
Loose footing
Structural issues
Failing bearing
Rubbing impeller
Dragging blade
Cavitation
Loss of lubrication
Loss of coolant flow
Electrical issues
Excessive load
Fault category Impact
Crashes
Striking

Fatigue
Mechanical issues
Assembly issues

Friction
Rubbing
Grinding
Temperature
Over heating
Sensor measurement Acceleration peak
(a-Peak)
Average velocity
(v-RMS)
Average acceleration
(a-RMS)
Degrees Celsius
(C)

Monitoring methods

Each VV sensor comes with factory-set alert outputs optimized for out-of-the-box performance based upon machine size and speed. Alarming thresholds adhere to recognized standards (ISO 10816) and ifm’s years of machine monitoring experience.

Part No. Machine optimization

VVB010

Fast ( > 600 rpm) and large ( > 400 hp)

VVB011

Slow (120…600  rpm) and large ( > 400 hp)

VVB020

Fast ( > 600 rpm) and small ( < 400 hp)

VVB021

Slow (120…600  rpm ) and small ( < 400 hp)

VVB001

Industrial machines

Location of sensors and monitoring methods

Typically, we recommend mounting sensors radially to shaft rotation to detect the greatest level of movement and located mechanically as close to the target as possible. The orange dots in the images indicate approximate sensor location.

Machine No. of sensors Sensor location Alarms Root issue

Axial fan

1

Radial H-DE motor

a-Peak

v-RMS

a-RMS

Temp

Impact

Looseness

Friction (bearing)

Overheating

Legend:  a = acceleration, v = velocity, H = horizontal, DE = driven end

Machine No. of sensors Sensor location Alarms Root issue

Radial direct drive fan

2

Radial H-DE and V-NDE motor

a-Peak

v-RMS

a-RMS

Temp

Impact

Looseness

Friction (bearing)

Overheating

Legend:  a = acceleration, v = velocity, H = horizontal, V = vertical, DE = driven end, NDE = non-driven end

Machine No. of sensors Sensor location Alarms Root issue

Radial indirect driven fan

4

Radial H-DE and V-NDE motor and fan shaft

a-Peak

v-RMS

a-RMS

Temp

Impact

Looseness

Friction (bearing)

Overheating

Legend:  a = acceleration, v = velocity, H = horizontal, V = vertical, DE = driven end, NDE = non-driven end

Machine No. of sensors Sensor location Alarms Root issue

Centrifugal pump

4

Radial H-DE and V-NDE motor and pump shaft

a-Peak

v-RMS

a-RMS

Temp

Cavitation

Looseness

Friction (bearing)

Overheating

Legend:  a = acceleration, v = velocity, H = horizontal, V = vertical, DE = driven end, NDE = non-driven end

Machine No. of sensors Sensor location Alarms Root issue

Electric motor

2

Radial H-DE and V-NDE motor

a-Peak

v-RMS

a-RMS

Temp

Impact

Looseness

Friction (bearing)

Overheating

Legend:  a = acceleration, v = velocity, H = horizontal, V = vertical, DE = driven end, NDE = non-driven end

When applying real-time continuous monitoring, 3-axis measurements are typically not needed. 3-axis techniques are typically used in traditional route-based analysis methods where only a snapshot of the machine health is recorded. In some cases where machine design implements axial loading, a second axial sensor may be necessary.

Integration

The VV family is flexible enough to provide varying degrees of control so it can scale as your level of IIoT integration grows. From sensor to ERP.

Stand-alone switching
With a 24 VDC power supply, the VV provides simple switching outputs for machine control and / or local indication of machine status.

IO-Link system
Adding sensors to your existing IO-Link network provides a quick way to achieve Industry 4.0, IIoT and RtM.

Available cyclic data:

  • Acceleration peak (a-Peak)
  • Average velocity (v-RMS)
  • Average acceleration (a-RMS)
  • Surface temperature
  • Crest factor

Available acyclic data:

  • Peak values of all 4 vibration process values
  • Minimum and maximum temperature values
  • Hardware and parameter errors

PLC integration to higher-level systems

Collect and evaluate IO-Link measurement values in standard PLC control. Optionally, transfer data to SCADA, MES or other plant control systems.

Available cyclic data:

  • Acceleration peak (a-Peak)
  • Average velocity (v-RMS)
  • Average acceleration (a-RMS)
  • Surface temperature
  • Crest factor

Available acyclic data:

  • Peak values of all 4 vibration process values
  • Minimum and maximum temperature values
  • Hardware and parameter errors

Independent data collection system

Collect the raw vibration signal as a BLOB (Binary Large Object) data set and manipulate it as desired. Create an independent monitoring network for notification and visualization.

  • Machine trending
  • Condition change
  • Email and text alert messages
  • Analytics and data science