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AI self learning-enabled condition monitoring

机译:AI支持自学习的条件监控

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摘要

Following years of collaboration with Innovate UK and the University of Strathclyde on gathering data, running algorithms and profiling diesel generators, as well as spending a good deal of time on design development and testing, Datum Electronics has announced its artificial intelligence (AI)-enabled condition monitoring technology, aimed at improving fuel efficiency and reducing maintenance and operational costs. The company claims that Datum Hawk is the future of condition monitoring, offering real-time analysis of power output, engine speed, torque, fuel flow, specific fuel oil consumption (SFOC) and much more. At 2000 samples per second, the system can detect problems quickly and display valuable information for each cylinder of the engine separately, providing customers with an up-to-date engine status. By incorporating AI self-adaptive algorithms, Datum Hawk is designed to greatly improve the lifespan and longevity of engines.
机译:在与创新英国和斯特拉斯科利大学采集数据,运行算法和仿形柴油发电机的多年,以及花费有很多时间的设计开发和测试,基准电子宣布了其人工智能(AI) - 重组 状态监测技术,旨在提高燃油效率和降低维护和运营成本。 该公司声称,DATUM鹰是病情监测的未来,提供功率输出,发动机速度,扭矩,燃料流量,特定燃油消耗(SFOC)的实时分析等等。 每秒2000个样本,系统可以快速检测出现问题并分别为每个汽缸显示有价值的信息,为客户提供最新的发动机状态。 通过合并AI自适应算法,Datum Hawk旨在大大提高发动机的寿命和寿命。

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