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 |
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 |
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