Web Based Artificial Intelligent Condition Monitoring System

基于网络的人工智能状态监测系统

• 批准号: 103645
• 金额: $ 25.95万
• 依托单位: MONITION LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=103645
• 关键词: Web; Based; Artificial; Intelligent; Condition

Condition Monitoring (CM) in industry identifies significant changes in a machines performance which could be indicative of developing faults. Many organisations use CM in some form however, according to Plant Services Magazine, current ‘rule’ & ‘case’ based CM is far from optimal since it remains problematic to combine & analyse the array of sensor data due to the variability in (1) the plant equipment; (2) systems componentry; (3) types of failure; (4) operating cycles; (5) operating temperatures; (6) lubrication; (7) & many other factors. As data & processing power becomes ever cheaper and more accessible remotely, there is an opportunity in developing the ‘next generation’ of CM technologies. According to Europe 2020 Factories of the Future report, modelling machine & process simulation is deemed the future tool for predictive maintenance. The application & fusion of Artificial Intelligence with current case & rule-based reasoning methods would allow for new & far superior CM solutions to be engineered. Benefits to end-user organisations include: (1) timely scheduling of maintenance increasing equipment reliability; (2) proactively taking actions to prevent & predict failure; (3) increase asset lifespan; (4) reduced downtime leading to 3-fold increase in production per line; & (5) provide at least 10% energy savings for 55% of all industrial users.

工业中的状态监测（CM）识别机器性能的显著变化，这些变化可能指示正在发生的故障。然而，许多组织以某种形式使用CM，根据Plant Services杂志，当前的基于“规则”和“案例”的CM远不是最佳的，因为由于（1）工厂设备;（2）系统部件;（3）故障类型;（4）操作周期;（5）操作温度;（6）润滑;（7）系统部件的可变性，联合收割机组合和分析传感器数据阵列仍然存在问题。（7）其他因素。随着数据和处理能力变得越来越便宜，越来越容易远程访问，开发“下一代”CM技术是一个机会。根据欧洲2020年未来工厂报告，建模机器和过程模拟被认为是预测性维护的未来工具。人工智能与当前案例和基于规则的推理方法的应用和融合将允许设计新的和更上级CM解决方案。对最终用户组织的好处包括：（1）及时安排维护，提高设备可靠性;（2）主动采取措施预防和预测故障;（3）延长资产寿命;（4）减少停机时间，使每条生产线的产量增加3倍;（5）为55%的工业用户节省至少10%的能源。