Machine learning system and data fusion to optimize layout conditions to detect corrosion under insulation

摘要

A system for predicting under-insulation corrosion (CUI) in an infrastructure asset includes at least one infrared camera positioned to capture a thermal image of the infrastructure asset, and supporting at least one infrared camera and electrically connected to the infrared camera. And at least one smart mount, wherein the smart mount includes a wireless communication module, a memory storage, a battery module that operates to recharge at least one infrared camera, an ambient sensor module configured to obtain ambient state data, and CUI-related from the infrastructure assets. And a structure probe sensor configured to acquire data. At least one computing device includes a wireless communication module that communicates with at least one smart mount, and is configured with a machine learning algorithm that outputs a CUI prediction for an infrastructure asset. The cloud computing platform receives and stores the received data and prediction output, and receives verification data for updating machine learning algorithms stored in the computing device.