Leveraging IoT for Condition Monitoring in a Large Power Utility

• 网络与连接 - WiFi
• 传感器 - 振动传感器

• 电网
• 玻璃

• 维护

• 资产健康管理 (AHM)
• 预测性维护

夏威夷的一家大型电力公司正在寻求对其设备平衡 (BOP) 发电资产进行更频繁的状态监测。

他们在预定的季度周游状态监测路线之间经历了重大的设备故障。

未披露

该公司是夏威夷的一家大型电力公司，经营着多个天然气发电厂的联合循环。

他们决定在 8-10 台设备上试用 Petasense 技术，包括一台关键锅炉给水泵 (BFP)、电机、几个冷凝泵、热滴泵、辅助冷却水泵和六台强制通风机。

他们在这些机器上安装了 20 个三轴电池供电的振动传感器 (Motes) 以及 WiFi 连接。安装在一天内完成，他们开始使用基于 Web 的 ARO Cloud 软件跟踪振动。技术人员和可靠性工程师还下载了 iOS 应用程序，以便随时随地访问资产数据。

• The implementation of the Petasense technology and the continuous condition monitoring approach brought about significant operational improvements for the power utility. The reliability engineers were able to detect deteriorating Asset Health scores and increasing vibrations on the Boiler Feed Pump Motor within a few days of installation. This early detection allowed them to identify a defect quickly and take corrective action before it could lead to a failure. The technology also provided the engineers with peace of mind, knowing that they would be able to detect the earliest changes by monitoring every hour. The combination of the Asset Health score with the detailed vibration analysis capabilities demonstrated a quick Return on Investment from implementing wireless Predictive Maintenance for the customer.

• The installation of the Petasense technology was completed in a single day, significantly reducing the time required for setup.
• The monitoring frequency was increased to once per hour, ensuring that any changes in vibration would be detected promptly.
• The technology helped prevent unplanned downtime by detecting a defect in the Boiler Feed Pump Motor before it could lead to a failure.