Artificially Intelligent Monitoring System for Airport Baggage Handling Assets (AIMS)

处理不当的行李给乘客带来痛苦，对航空业来说代价高昂(估计每年17.6亿英镑)。2017年)，并损害了声誉。据估计，由于行李处理设备的故障，希思罗机场每1000个行李中就有1.6个处理不当。每天14万名乘客，每个行李100 GB的补偿相当于航空公司每天损失22,400 GB。作为回应，希思罗机场设定了“每位乘客，每个行李，每次”的目标，行李系统的停机时间不到一个半小时。不幸的是，大多数常见的故障，通常是电动变速箱单元(MGU)或传送带的故障，需要一个多小时才能修复。唯一的选择是在夜间停机期间进行维护。这通常也是不可能的，因为在设备故障严重到需要计划外关闭之前，没有预先警告。存在复杂的状态监测系统，但它们仅用于高资本价值的关键资产，因为它们太昂贵，无法大规模部署(希思罗机场约30,000 MGU)。振动监测系统是最好的系统之一，因为它提供有关关键机械部件(如齿轮、轴承和电机)损坏以及错位、不平衡和裂纹等故障的丰富信息。预测振动监测所需的高质量加速度计成本约为500 GB，这对于在机场广泛部署是站不住脚的。不幸的是，低成本的加速度计不能很好地检测早期损伤。电机电流特征分析(MCSA)可能是一种有效的、低成本的替代方案。目前，由于现有电机电流数据信号处理算法的局限性，AIMS还存在诊断能力差的问题。AIMS将通过开发以下新的信号处理来克服这一挑战：a)使用低成本电流钳从电机电流数据中提取对齿轮、传送带、轴承、电机和轴的早期损伤和故障的高保真诊断特征。B)一种新的人工智能，能够对MGUS/传送带的健康状况进行分类。该系统的输出将用于为工程师创建易于解释的行李搬运、资产健康和优先维护行动的交通灯显示。该系统将在机场和涉及快速消费品(FMCG)和仓储等机械处理的行业中得到广泛应用。AIMS将释放机会，在5年后项目期内产生(折扣)2190万GB的毛利润。26/04/21-更新范围，将项目试验从希思罗机场改为斯基波尔机场

Mishandled bags create misery for passengers, are expensive for the airline industry (estimated at £1.76b p.a. in 2017), and damaging to reputations. An estimated 1.6 per 1000 bags are mishandled at Heathrow due to faults with the baggage handling equipment. 140k passengers per day and compensation of ~£100 per bag equates to airlines losing £22,400 a day. In response, Heathrow has set an objective of "Every passenger, every bag, every time" and baggage systems down-time of less than 1/2 hour.Unfortunately, most of the common failures, typically of a motor gearbox unit (MGU) or conveyor, take more than an hour to repair. The only option is to carry out maintenance during the nightly shut-down. This is not usually possible either, because there is no advance warning of equipment faults before they are serious enough to require un-planned shutdowns. Sophisticated condition monitoring systems exist, but they are only used for high capital value, critical assets because they are too expensive to deploy on a large scale (~30,000 MGUs at Heathrow).One of the best systems is vibration monitoring, because it provides a wealth of information on damage to critical machine parts such as gears, bearings and electric motors as well as faults such as misalignment, imbalance, and cracks. High quality accelerometers required for predictive vibration monitoring cost ~£500, which is untenable for widespread deployment at an airport. Unfortunately, low cost accelerometers do not perform well enough to detect early stage damage.Motor current signature analysis (MCSA) could be an effective, low cost alternative. Currently, it also suffers from poor diagnosis capability due to limitations of present signal processing algorithms for motor current data.AIMS will overcome this challenge by developing: a) Novel signal processing to extract high fidelity diagnostic features for early stage damage and faults to gears, conveyors, bearings, motors and shafts from motor current data using low cost current clamps. b) A novel artificial intelligence that is able to classify the health of MGUs/Conveyors. The output of this system will be used to create an easy to interpret traffic light display of baggage handling asset health and prioritised maintenance actions for the engineers. The system will have widespread application in airports and industries involving mechanical handling such as fast moving consumer goods (FMCG) and warehousing. AIMS will unlock the opportunity to generate (discounted) gross profits of £21.9m in a 5 year post project period.26/04/21 - update to scope to change project trials from Heathrow to Schipol airport