L2M NSERC- Machine Learning Based Tool to Predict Possible Failure Type of Oil and Gas Pipelines

石油和天然气管道基础设施市场遭受由不同因素引起的连续管道故障事件。对油气管道失效事件进行真实的或接近真实的量化，有助于制定更快、更合理的应急预案。因此，本建议的目的是开发一个数据驱动的管道故障评估产品，它结合了人工智能技术，并利用公共可用的故障数据库。Lab2Market计划将帮助提供工具和专家，让研究人员了解评估最终用户潜在需求所需的适当市场研究技能。

The oil and gas pipeline infrastructure market suffers from continuous pipeline failure events which is causedby different factors. Quantifying failure events of oil and gas pipelines in real- or near-real-time facilitates afaster and more appropriate response plan. Hence, the aim of this proposal is to develop a data-drivenpipeline failure assessment product, which incorporates artificial intelligence technology and utilizes publiclyavailable failure databases. The Lab2Market Program will help in providing access to tools and experts that informs researchers about appropriate market research skills required to assess potential needs by end-users.