Tribo-Acoustic Sensors for In-Situ Performance and Inspection of Machine Components

Engineering machines, from car and planes, to power stations and production lines, have lots of moving parts. The reliability of these parts is key to the function and energy efficiency the machine. It is often these moving parts that fail and frequently that failure is associated with the rubbing surfaces. Machine elements like bearings, gears, seals, and pistons often wear out, exhibit high friction, or seize.

Knowing if a machine element is performing at its optimum can save energy and lead to long life. Being able to monitor the components in-situ in a machine can speed up the development cycle time. Further, monitoring performance rather than failure, allows allows the machine operator to plan maintenance. This is particularly important for high capital cost machines, in remote locations, like offshore wind turbines.

Current monitoring methods are based around measuring excessive vibration or the noise emitted by a failed component (acoustic emission AE) or by counting wear debris particles in a lubricant. Sensors that measure performance rather than failure, and so can be used to optimise operating parameters would be much more useful. This also opens the possibility of using advanced control based on sensor readings, Many machine components are commodities, and integrating sensors provides a way to add value to what would otherwise be a commodity product.

The Leonardo Centre at Sheffield has developed unique methods for measuring machine contacts in-situ. The approaches are based on ultrasonic technologies adapted from the NDT and dynamics communities. By sending ultrasonic pulses through machine components and measuring transmission and reflection we have been able to non-invasively study various tribological machine components. In early work we developed methods to measure the oil film thickness, and the amount of metal contact. This has been well established, validated in laboratory experiments, and applied to journal bearings, trust pads, rolling bearings, pistons, and seals. Several industrial companies have adopted these approaches in their product development cycles.

This fellowship seeks to explore new methods to learn more about contacts. Buy using different kinds of ultrasonic waves, transducer topologies, and signal processing we will develop methods to measure contact load, stress history, oil viscosity, and friction. These will be prototyped in the laboratory and we have industrial partners ready to provide field applications. In addition the fellowship seeks to collaborate with academic institutions; firstly to learn new acoustic sensor techniques and secondly to support research into machine element research with the provision of new measurement methods.

This will support the Leonardo Centre aim to be, not only the leading centre for ultrasonic measurement in tribology, but to be a key part of the UK's research infrastructure in machine component research and development both in industry and academia.

The industrial beneficiaries of this research will be machine element manufacturers and major equipment suppliers, owners and operators. Potentially this could be across all industrial sectors; but principally high value products where sensor installation is cost effective, for example offshore wind, power generation, offshore oil and gas, and aerospace.

Five examples are given:
1. Wind Energy Industry. Wind power is still relatively expensive and much of this cost is associated with on-going maintenance. Wind turbine bearings for example are subject to complex loading and current lifetimes are short (5 years typical for gearbox bearing). Advanced sensor system could be used to monitor film thickness and load and detect when failure is likely and remaining useful life.

2. Power Generation. Load and air based gas turbines transit thrust through hydrodynamic bearings. These are unmonitored and their operation is not optimised during running. Sensing the bearings on the test stand could help to reduce size and weight by ensuring the individual elements carried exactly the right load at the right lubrication condition. In the longer term sensing during flight could be used to optimise their performance and hence fuel efficiency.

3. Aircraft Landing Gear - pin joints that allow articulation of the structural parts. When are the joints likely to fail, how can they best be monitored in the event of a hard landing.

4. Combustion Engines Industries. There is a global drive to improve engine efficiency and reduce emissions. Sensing of machine parts (engine bearings, piston/liner) has great value in optimising engine performance. For example, large marine diesel engines consume (i.e. burn) as much as 1 tonne of lubricating oil and 250 tonnes of fuel per day. Building a sensor system that exactly regulates lubricant flow just when it is need could significantly reduce the financial and environmental costs of operation.

5. Metal Rolling Industry. Metal rolls are largely commodity products; most R&D in the industry is based around material improvements that marginally increase wear resistance. The provision of internal sensing capability into a metal roll to monitor load, stress, lubrication, wear and surface roughness would create a functionally more useful product and add value through technology.

Impact to the nation is through increasing the competiveness of UK products. Many machine components are commodity products. One way to add value to the component is to through embedded technology. This might be in terms of component design features, or by using advanced materials. Alternatively it can be through the use of on-board monitoring and feedback. Commercial value can be added by selling a monitoring and control system along with the low-cost machine element. This requires the in-situ sensing capability that is a deliverable of this fellowship.

Indirectly, nationwide impact is achieved through the availability of lower cost energy and reduced greenhouse gas emissions. This is through the more efficient use of natural resources. A well-designed machine element operating at its optimum point is smaller, lighter, lasts longer, and consumes less energy. In-situ sensing enables that design and operating optimisation.