技术
- 分析与建模 - 边缘分析
- 分析与建模 - 预测分析
- 功能应用 - 远程监控系统
- 传感器 - 压力传感器
- 传感器 - 振动传感器
适用行业
- 公用事业
适用功能
- 维护
用例
- 预测性维护
客户
那霸发电厂
关于客户
Nabha 发电厂是一座 700 兆瓦的超临界火力发电厂,位于印度旁遮普邦拉杰普拉附近。对于如此规模的工厂来说,计划外的维护停机会对生产力和盈利能力产生重大影响。
挑战
冷凝冷却水 (CCW) 泵是维持稳态运行的关键泵之一,它是一种卧式叶片泵,运行速度高达 1650 m3/hr,排放压力为 9 MPa (62 psi),转速为 986 rpm。该泵每天离线都会使工厂损失 250,000 美元的收入,并且每次故障都要花费数万美元来执行计划外的维修。因此,Larsen & Toubro (L&T) 确实需要一种预测性维护解决方案来及早发现故障并提供可靠的剩余使用寿命 (RUL) 预测
解决方案
我们提出了我们的 RotationLF 系统,我们在该系统下安装了大约 24 个无线传感器,作为空气压缩机、ACW 和 CCW 泵以及风扇试点项目的一部分。
选择 VibrationLF 传感器的具体位置来监控:
1) 非驱动侧轴承,电动机
2) 驱动侧轴承,电动机
3) 驱动侧轴承、泵
4) 非驱动侧轴承、泵
安装后,强大的电池供电无线传感器开始监控泵和电机,并通过使用边缘和云计算的加密和安全网络将数据发送到我们基于 SaaS 的平台。收到数据后,RotationLF 平台使用高度复杂的算法进行数据分析。
安装传感器大约六周后,人工智能向 L&T 发出警报,指出泵上检测到叶片故障,导致气蚀。系统中描述的故障频率表示早期故障。
运营影响
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