Developing a machine integrated lube oil analysis system

开发机器集成润滑油分析系统

• 批准号: 10005098
• 金额: $ 20.75万
• 依托单位: RAB MICROFLUIDICS RESEARCH AND DEVELOPMENT COMPANY LIMITED
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10005098
• 关键词: Developing; machine; integrated; lube; oil

Reliability and availability of shipping vessels is critical to quality of life and impacts significantly on cost of goods consumed globally. This is because the maritime industry is responsible for 90% of global trade, hence disruptions in maritime service impacts the way we live and how much we pay for our goods. Until now, it has been difficult to predict with any certainty machinery failure in shipping vessels. This has resulted in high rate of failure in rotating lubricated machinery such as engines. The high rate of marine engine failure is the leading cause of service disruptions in the maritime industry. However, such disruptions could be avoided with early detection of engine faults ensuring that engine failure is prevented.Diagnosing early, potential failure of marine lubricated equipment such as engines is critical to operation of a shipping vessel. RAB-Microfluidics has developed cutting edge microfluidic lab-on-a-chip technology to deliver real-time continuous testing and analysis of lubricating oil. Our "Lab-on-a-Chip" technology delivers oil analysis 1000x faster and 10x cheaper than the current "send the sample to the Laboratory" approach. Analysis of contaminants in engine oil, gearboxes, etc. is a well-established method of detecting problems. This procedure is called Oil Condition Monitoring. We deliver this onsite, in real time and this is a significant improvement on the current practice of sending the sample to onshore laboratories for analysis thus saving cost and improving machinery reliability and vessel availability. We combine our hardware technology with data computing by developing machine learning capabilities to utilise the big data generated from our hardware. This offers real-time continuous monitoring, early problem diagnosis, rapid decision making, enhanced efficiency and cost savings.This project seeks to develop this core technology further and build a field prototype demonstrator that integrates with a live operational marine engine. This will ensure we fully demonstrate the automation of our novel Oil Condition Monitoring process. This will be a first-of-its-kind development with potential to dramatically improve shipping vessel reliability and availability by ensuring developing faults of key equipment are identified early. If successful, our technology will herald a game changer for the maritime sector and would invariably have a ripple effect on our quality of life by ensuring reduced marine service disruptions. There is also the added possibility of such success being reflected on the cost of good we consumed due to lower marine transportation costs.

船舶的可靠性和可用性对生活质量至关重要，并对全球消费的商品成本产生重大影响。这是因为海运业占全球贸易的90%，因此海运服务的中断影响了我们的生活方式和我们为商品支付的费用。到目前为止，很难确定地预测船舶中的机械故障。这导致了旋转润滑机械如发动机的高故障率。船舶发动机的高故障率是航运业服务中断的主要原因。然而，这种中断可以通过早期检测发动机故障来避免，从而确保防止发动机故障。早期诊断诸如发动机的船用润滑设备的潜在故障对于船舶的操作至关重要。RAB-Microfluidics开发了尖端的微流体芯片实验室技术，可对润滑油进行实时连续测试和分析。我们的“芯片实验室”技术提供的油分析速度比当前的“将样品送到实验室”方法快1000倍，成本低10倍。分析发动机油、齿轮箱等中的污染物是一种行之有效的检测问题的方法。此程序称为油液状态监测。我们在现场提供真实的时间，这是对目前将样品送到岸上实验室进行分析的做法的重大改进，从而节省成本，提高机械可靠性和船舶可用性。我们将联合收割机的硬件技术与数据计算相结合，开发机器学习功能，以利用硬件产生的大数据。该项目旨在进一步发展这一核心技术，并建立一个与现场运行的船用发动机集成的现场原型演示器。这将确保我们充分展示我们新颖的油液状态监测过程的自动化。这将是同类开发中的首创，有可能通过确保尽早发现关键设备的发展故障来显着提高船舶的可靠性和可用性。如果成功，我们的技术将预示着海事领域的游戏规则改变者，并将通过确保减少海事服务中断，对我们的生活质量产生涟漪反应。由于海运成本降低，这种成功也有可能反映在我们消费的商品成本上。