Poor bearing lubrication identified and immediately remedied

Here is a great example from James Sylvester of how visually helpful the new Emerson 2140 PeakVue Plus is while working on site.

On a recent survey of a critical 110KW blower motor we noticed the PeakVue levels had increased. While at the machine we quickly ran the PeakVue plus and this highlighted the issue as a poor lubrication condition.

Instead of writing this in the report then living in hope the motor is correctly greased, we showed this at the machine to the site fitter and we were immediately permitted to lubricate the bearings and the levels reduced.

PeakVue Plus was great as we did not have to upload to the laptop to explain. We just showed them the colour chart indicating poor lubrication and they acted upon it there and then.

Our PeakVue Stress Wave Analysis Wall Chart consists of 12 detailed real world faults, captured using PeakVue Technology.

110KW Motor RMS
Image of the 110KW critical blower motor

Initial onsite PeakVue Plus RMS
Image of the 2140 at the machine with the Lubrication issue highlighted.

Book an Onsite Vibration Analyser System User Course. 2 or 4 day hands-on course. Focuses on the basic operation of MHA’s.

After lubrication onsite PeakVue Plus RMS
Image of the 2140 at the machine after controlled lubrication

“PeakVue Plus prescribes to the user the necessary corrective actions to preserve bearing life and ensure long-term availability of their assets,” said Robert Skeirik, director of machinery health product management, Emerson. “It’s like having an expert available at the touch of a button.”

The vibration data was then uploaded to the MHM software for analysis

Vibration data reduction RMS
Max PeakVue Trend

Multiple Routes Spectra RMS
PeakVue Spectra and Time waveform Data

The AMS 2140 Machinery Health Analyser takes vibration data and analysis measurements to the next level.


PeakVue Plus enables the AMS 2140 Machinery Health Analyzer users to see at a glance not only whether a machine is in good working condition, but also the severity of an issue and whether it’s related to a bearing defect or lubrication. This helps field technicians determine root causes and quickly resolve equipment problems before failures occur and cause unplanned downtime.

Its anything with a bearing – anything! Emerson’s PeakVue technology cuts through the complexity of machinery analysis to provide a simple, reliable indication of equipment health via a single trend. PeakVue filters out traditional vibration signals to focus on impacting, a much better indicator of overall asset health on any type of rolling element bearing machine.

We do indeed! Students can choose from ISO 18436-2 CAT I to CAT IV. Courses are certified by BINDT or Mobius Institue. Study options include: Online, Public and Onsite. See the Vibration Analysis Courses page for more details.

Flue Gas Recycle Fan: Introduction

The Flue Gas Recycle Fan is part of the COGA unit. The fan increases the efficiency of the COGA unit by recycling a proportion of the incinerated gases from the COGA stack. The fan is critical in sustaining high rates of operation on the plant, catastrophic failure of this fan would result in a COGA unit shut down. This would increase the emissions to the atmosphere and heavy fines could be imposed by the Environment Agency.

Flue Gas Online Vibrartion Points

The above Photo illustrates the position of the fixed online vibration sensors that are fitted to the fan and motor (i.e. MNV = Motor Non Drive End Bearing Vertical).

Flue Gas Fan Vibration Frequencies

The above diagram shows the configuration of the flue gas fan. The above configurations, speeds, bearing details etc have being entered into the online system to assist in fault diagnostics.

In Mid May 2002 the Flue gas fan sensor (Fan Non Drive End Fan Horizl) entered into an alarm condition, the system automatically started rapid data collection. Two parameters were initially in alarm PK-PK Waveform, (Peak to Peak Value of time waveform measured in G’s) and a Bearing energy band also measured in G’s. Below is the Online watch screen showing the status of monitored plant.

Flue Gas Online Watch Screen

Flue Gas Fan Trend Display Waveform

The above online trend is taken off the Fan Non Drive End Sensor;  note how quick the fault is deteriorating. Planning windows are rare on the COGA unit due to the environmental consequences if the plant is shut down.

The next step is to analyse the data to pinpoint why the vibration levels were increasing. Spectrum and Time Waveform analysis was used for this. Below is a spectrum taken from the online system. (Fan Non Drive end horizontal Bearing.)

Flue Gas Fan Bearing Vertical

The filtered spectrum above indicates a problem with the cage and rollers on the NDE fan bearing, a clear match is made with the cage ( 0.4 orders ). 2X Roller spin freq is also present due to defects on the rollers impacting the inner and outer races as they rotate. Cage defects are well known to deteriorate quickly.

Flue Gas Fan Bearing Vertical 2

The time waveform shows impacting to 78 G’s, severe bearing damage.

After discussions with production and maintenance, the reliability team decided to plan for the fan bearings to be changed at the earliest opportunity. New bearings were ordered and a scaffold erected ready for a quick bearing change. The opportunity came on the 21st May when the Dryer Plant shut down on an overload issue. The COGA was still running at this point, so a plan was formulated to shut the flue gas fan down in controlled manner so that the COGA unit could still be run, but at reduced rates, this was only possible because of the Dryer plant shutting down.

Flue Gas Fan Trend Display Waveform PK PK

Flue Gas Fan Bearing

Upon inspection of the bearing it was found that the cage had disintegrated and the bearing had entered the final failure mode. The fan would have failed catastrophically later that day, this would have caused major shaft and fan damage. The bearings were replaced and the fan was running within 6 Hours.

The cleaned up NDE cooper fan bearing showing remains of the cage and the damaged rollers.

Flue Gas Fan Bearing 2

Estimated Cost Savings

(Using Best Practice)

Actual Costs (Action Taken)

Parts : New Bearings  Coo 01400 x 2 = £ 500

Labour : 2 men , 6 hours @ £ 30/ hour = £ 360

Production Losses: None, job planned in with Boil Out

Total Cost = £  860

Costs (No Action Taken)

40% of ERV (Estimated replacement value)

0.40 x £ 55000 (Cost of New Fan) = £ 22,000

Labour : 2 men, 48 hours @ £30 /hour = £3500

Environmental Effect (Fines)

3 Days to remove/repair/replace flue gas fan

If no credits/ Fines Potential £ 2 Million a /day

Production Loss / running on lower rates.

3 Days on lower rates £ 26012

Total Cost  = £ 47978

Estimated Avoided Cost = £ 51512

Final Note

This case study highlights the fact that cage defects can rapidly deteriorate; in this case it only took 5 Days. This type of fault is often missed using conveniently walk round programs; continuous monitoring is sometimes the only way to pick these faults up.


The fan is critical in sustaining high rates of operation on the plant, catastrophic failure of this fan would result in a COGA unit shut down. This would increase the emissions to the atmosphere and heavy fines could be imposed by the Environment Agency.

This case study highlights the fact that cage defects can rapidly deteriorate; in this case it only took 5 Days. This type of fault is often missed using conveniently walk round programs; continuous monitoring is sometimes the only way to pick these faults up.

John Stubbs, Geoff Copeland, Stuart Walker, Chris Bennet, Dean Whittle, David Shevels


stuart walker bio rms 2020

 Stuart Walker has worked in the Condition Monitoring and Reliability sector for the last 23 years. He started his career working for Dupont as a Mechanical and Production Technician after completing a four year apprenticeship. It was here he was introduced to Condition Based Monitoring and setup a successful program at one of DuPont’s UK sites. He utilized technology’s such as Vibration analysis, Oil Analysis and IR Thermography moving the site from a time based maintenance strategy to a predictive and proactive one. Stuart then worked for a Reliability Consultant company for a number of years implementing and running a number of other successful CBM programs across the UK.

In 1999 he setup Reliability Maintenance Solutions Ltd with his colleague Dean Whittle. Together they have successfully grown the company over the last 20 years. RMS provides reliability consultancy, training, service, and products to a number blue chip companies across the UK, Europe and Middle East. Stuart has worked in many industry sectors including Oil & Gas, Petrochemical, Power and Paper. He is currently working on projects introducing and implementing the new Motion Amplification Technology within RMS and across a wide range of Industries at home and abroad.

As part of the Innovate UK fund, over the past 2 years RMS have been involved in an ‘Intelligent Wireless Vibration System’ collaboration between the Building Research Establishment (BRE), Cybula, Griffiths Associates and Skanska. The project called REAM (Enabling remote built environment asset management using embedded intelligence) is tasked with enabling low-cost embedded intelligence within the Facilities Management (FM) market.

st barts hospital rms ai condition monitoring wireless vibrationThis is done by optimising Artificial Intelligence (A.I) technologies for use in detecting the pre-cursors of fault conditions arising on rotating plant. The landmark achievement of the project was during the pilot studies run at St. Barts Hospital and British Sugar where the system was capable of learning the behavior of the plant and successfully detecting anomalies in their condition. All completed on single board computing systems with no cloud server for computing power. Interestingly the system is capable of communicating over long distances with Wifi and other radio technologies but can take care of all its computing on the CPUs next to the machines.

rms ai british sugar factorywissington w256h182

The natural progression for this technology is certainly for use in the built environment enabling low cost condition monitoring using a variety of technologies. With that in mind the Innovate UK fund encourages projects such as this to seek commercial viability and opportunities, as such the pre-production prototype versions of the commercial system are now being trialed as manufacturing preparations are made.

The condition monitoring analytics, which have been developed in high integrity applications (such as nuclear, transport, and energy) for rapid and easily configurable abnormality detection of failure modes can also be run on more highly critical machines utilising more traditional data collection types. Firstly though, Skanska feel the future of Facilities Management (FM) is the use of multiple data sources through intelligent condition monitoring to enable more effective and efficient asset management.

The future of the project looks bright as it becomes a commercial product capable of increasing asset life, maximising efficiency, reducing risk of unexpected failures and reducing energy usage. The REAM project was nominated as a finalist for the “Best Asset Management Innovation” at the Building Innovation Awards.

Interested to know more about this exciting technology? Contact us to schedule a call on +44 (0)1206 791917 or via email to: info (at) rms-reliability.com.