1. Model-based V-I systems: - using your existing electric motors to tell you about your driven equipment’s condition Geoff Walker, Director, Artesis LLP MEETA

2. Title: Model-based Voltage and Current systems: A new type of tool for monitoring the condition and performance of your equipment – especially inaccessible or remote equipment – covering mechanical and electrical and operational problems. How to avoid unexpected breakdowns and make your maintenance more efficient.   Abstract:  This 15 minute talk will describe the capability of Model-Based Voltage and Current Monitoring systems, that use the electric motor driving your equipment as a sensor, to tell you what is going on inside the equipment. It will outline briefly how these systems work, what they are capable of, and use a number of case studies to illustrate the surprising depth of information that can be provided, covering mechanical and operational factors as well as electrical parameters.   Brief Biography:  Geoff Walker is a Mechanical Engineer who spent the first decade of his career in the Chemicals Industry as an engineer with ICI, managing maintenance, new projects and technology development. He spent the next decade working as a management consultant with Coopers & Lybrand / PWC, where he led their Physical Asset Management practice across Europe, Middle East and Africa, helping a wide range of industries to improve the performance of their Maintenance and Asset Management. He has spent the last decade using clever technology to provide automated fault diagnosis, and as a founding Director of Artesis LLP he is leading the deployment of Model-based voltage and current based solutions for condition monitoring, allowing companies to increase the footprint of assets to which Condition Based Maintenance can be successfully applied.

3. Structure  The level 1 problem – keeping your wheels going at least cost  The level 1 solution = CBM. No unexpected downtime. Least costs.  Problem at level 2: CBM isn’t easy  Technology  Cost  Culture  Solution at level 2: MCM  What it is, what it does, how it works  Egs in practice  What next : how to select, install, commission, use  Conclusion:  MCM allows you to improve performance, reduce costs, avoid unexpected downtime, improve efficiency.  It’s simple to install and simple to use  Try it!

4. The level 1 challenge How to keep existing, sometimes elderly, plant going at max performance and min cost, avoiding unexpected downtime Moving from BD to PM to CBM (PdM) is a frequently chosen route

5. Why Predictive? Breakdown maintenance Planned maintenance 50% breakdown maintenance 10% breakdown maintenance Predictive maintenance Cost

6. The level 2 challenge: getting to Predictive Adopting CBM / PdM is not easy: Technology? Cost? Culture / resource pressures Remember the level 1 challenge - How to keep existing, sometimes elderly, plant going at max performance and min cost, avoiding unexpected downtime

7. The level 2 solution: an easier way to get what you want NASA developed technology! – Model based V-I systems Use your existing motor as a sensor Just measure voltage and current (3-phases) Provides an astonishing amount of information on your equipment Electrical (insulation, rotor bars, stator windings, supply) Mechanical (eg imbalance / misalignment / bearing problems) Operational (eg cavitation, blocked filters, even tidal effects!)

8. How does it work? InstallLearnRun

9. What it is, what it does, how it works Voltage Input – shape / size Volts in Resulting current – shape / size Current Behaviour of system 1. Summary screen: Which machines have a problem? 1. Summary screen: Which machines have a problem? 2. Diagnostic screen: What’s wrong with them? What do I have to do? 2. Diagnostic screen: What’s wrong with them? What do I have to do? 3. Trend screen: How long do I have to act? 3. Trend screen: How long do I have to act? 4. Spectrum screen: Analysis background 4. Spectrum screen: Analysis background

10. Tech Case 1: typical example of MCM maintenance cost saving on water pumps – >90% less £  Series of pumps with history of catastrophic failure – needing complete replacement of pump and motor on each occasion  MCM detected developing deterioration and advised repair to pump (not detected by other techniques)  Pump was repaired at low cost (cold resin repair to casing, replacement of cheap wear rings)  Motor, shaft, bearings, impeller all re-used.  Cost and disruption a fraction of previous experience; a few hundred £ compared to several thousand £

11. Pumping Station Fuel Pump Misalignment Fuel Pump 4 th July; laser shaft alignment Trials of Shaft adjustments 3th July; Change of Oil Seal Maintenance QA verification

12. Advantages of model- based V-I systems  No sensors on plant  Easy to install  Great for inaccessible equipment  Not disturbed by maintenance activities  Easy to use  Easy to understand  Covers broad range of failure modes  Electrical, Mechanical and Operational  Fits with culture  Allows adoption of CBM: No unplanned downtime

13. Conclusions  MCM allows you to do good things:  improve performance,  reduce costs,  avoid unexpected downtime,  improve efficiency.  It’s simple to install and simple to use  Try it!

14. If you want to know more… Thankyou GeoffWalker Artesis LLP, St John’s Innovation Centre CowleyRoad, Cambridge CB4 0WS GeoffWalker Artesis LLP, St John’s Innovation Centre CowleyRoad, Cambridge CB4 0WS T 0845 634 3854 M 07989 547411 E geoff.walker@artesis.com GeoffWalker Artesis LLP, St John’s Innovation Centre CowleyRoad, Cambridge CB4 0WS GeoffWalker Artesis, St John’s Innovation Centre CowleyRoad, Cambridge CB4 0WS T +44 (0) 845 634 3854 M +44 (0) 7989 547411 E geoff.walker@artesis.comgeoff.walker@artesis.com

15. What it is, what it does, how it works Voltage Input – shape / size Volts in Resulting current – shape / size Current Behaviour of system Current in motor depends on volts supplied and whatever is going on in the motor and driven equipment system Distortions to current NOT coming from voltage therefore show behaviour of system Frequency analysis of these distortions gives outputs similar to vibration monitoring, with characteristic frequencies identifying causal phenomena