Hydraulic fluid power is widely used in land, sea and air transportation, construction machinery, industrial machinery, agricultural machinery, oil and gas, mining and defence. However hydraulic systems are inherently very noisy and new techniques for fluid-borne noise (FBN) attenuation are needed to achieve acceptable and safe noise levels as documented in The Health and Safety Executive 'The Control of Noise at Work Regulations 2005'. It is obvious that low-noise hydraulic machines can significantly improve people's working environment and quality of life. Hydraulic systems are often inefficient with an average efficiency of 21%. An average 5% improvement in efficiency can save 0.51 quadrillion Btu of energy and US$10.1 billion while reducing carbon dioxide emissions by more than 33.95 million metric tons, according to the recent study of 'Estimating the Impact (Energy, Emission and Economics) of the US Fluid Power Industry, 2011'. Some new techniques such as 'digital' fluid power promise much lower energy losses but are hampered by higher noise levels according to the findings from the recently completed research project (EPSRC grant EP/H024190/1). Effective noise control techniques should enable use of these more efficient hydraulic systems, resulting in considerable reduction in fuel consumption and carbon dioxide emissions. The noise in hydraulic circuits presents itself as FBN, structure borne noise and air borne noise. FBN is caused by the unsteady flow produced by pumps and motors or 'digital' hydraulics, and propagates through the system causing vibration or structure borne noise, which in turn causes air borne noise. Traditional noise control measures can lead to additional power losses. Unwanted noise also consumes energy and generates heat which may lead to machines instability and failures. In response to the engineering challenges in noise control and energy efficiency, this proposal is a timely investigation into a novel integrated noise attenuation system for hydraulic machines. The proposed research would be a world first, and will apply a newly integrated noise control approach engaging both active and passive control methods to obtain an effective, robust and high-bandwidth noise attenuation for fluid power systems. Uniquely, this new approach allows the dominant harmonic pressure pulsations to be attenuated by the active attenuator and high frequency noise to be cancelled by passive tuned flexible hoses without impairing the system dynamic response. This novel methodology can significantly improve the noise attenuation performance. Simulations of a generic integrated FBN control system studied by the PI show that 55dB attenuation was achieved, while 40dB was achieved by only using the active control method and 20dB was achieved by using the passive control approach, respectively. The research outcomes will deliver effective solutions to replace traditional noise control equipment and provide input into the development of quieter fluid power machines in the UK and worldwide. The experimental results will provide confidence in applying the integrated FBN control system and design methodology for both conventional and 'digital' hydraulic machines. This research will maintain my research group's unique world leading position and accelerate research impact to ensure the UK remains internationally competitive. This work will ensure the UK's significant role in the global market for hydraulic components which is projected to reach US$67.8 billion by 2020 and further enhance the UK's leading position in the European hydraulic market. It will also help ensure that the UK is well equipped to deal with noise challenges in hydraulic engineering and has the research capability and quantitative skills for worldwide environmental and energy challenges it may face in the future.
|Effective start/end date||1/05/17 → 31/12/19|
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):