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National Grid's Successful Damage Reduction Strategy with Urbint's AI-Powered Solution
技术
- 传感器 - 气体传感器
- 传感器 - 电表
适用行业
- 电网
- 公用事业
用例
- 微电网
- 结构健康监测
挑战
国家电网通过实施普遍的地下损坏预防最佳实践，降低了其损坏率，该指标显示了纽约州北部地区每 1,000 811 张罚单的损坏数量。 2006 年公用事业公司的损坏率为 5.36 次/千人次，2014 年为 1.89 次/千人次，提高了 65%。然而，经过几年的进步，该公用事业的损坏率趋于稳定。
与许多公用事业公司一样，国家电网也只有有限的工作人员来处理大量的票务。此外，该公用事业公司在长岛遭受了高于平均水平的未致电损失。
National Grid 需要一种方法来有效地识别最高风险的挖掘工作，以便他们能够最好地分配他们的小团队。他们还需要帮助确定长岛最有可能不会发生呼叫损坏的地方，以便他们能够最好地针对他们的 811 宣传活动。
客户
国家电网
关于客户
National Grid是一家跨国电力和天然气公用事业公司，总部位于伦敦，在美国东北部的三个州开展业务：纽约、马萨诸塞州和罗德岛。该公用事业公司位于纽约州北部的地区，包括纽约市的大部分地区和长岛的全部地区，为 190 万天然气客户提供服务，并拥有 12,000 英里的天然气输配管道。
Robert Terjesen 负责管理纽约州北部的气体损害预防计划。他的团队由四名经理、20 名检查员、200 名定位员和 17 名合同“损害预防顾问”组成。该地区平均每年有近 600,000 811 张门票。
解决方案
National Grid 与 Urbint 合作实施 Lens for Damage Prevention，这是一种人工智能软件，可识别高风险挖掘。 Urbint Lens 检查公用事业公司的历史事件数据以及资产的使用年限、类型和位置等内部数据，并将其与 Urbint 的世界模型相结合，该模型表示围绕和影响地下资产（包括土壤条件）的外力、海拔、天气、人口密度和建筑——将风险评分分配给 811 票。
Urbint Lens 发现 National Grid 的大部分损失仅来自他们的一小部分罚单，而最强有力的损失预测因素之一是哪家挖掘公司在进行挖掘。凭借这种洞察力，国家电网能够针对问题挖掘机并主动干预有风险的工作现场。
为了减少长岛的无人召唤挖掘损坏，国家电网转向了 Urbint Lens 的无人召唤功能。 Urbint Lens for Damage Prevention 是唯一一款可提供关于可能发生非票证挖掘的地点以及最有可能导致基础设施损坏的地点的损坏预防软件。
运营影响
数量效益
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