Koch Industries. has filed a patent for a system and method for corrosion and erosion monitoring of pipes and vessels. The technology combines ultrasonic thickness monitoring with area monitoring to detect localized damage. Additionally, the patent includes a method for down-selecting probe assemblies for optimized asset health monitoring. GlobalData’s report on Koch Industries gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Koch Industries, Digital lending was a key innovation area identified from patents. Koch Industries's grant share as of January 2024 was 64%. Grant share is based on the ratio of number of grants to total number of patents.
Corrosion and erosion monitoring system for pipes and vessels
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A patent application (Publication Number: US20240036011A1) describes a method for down-selecting probe assemblies on a piping system for pipe wall thickness monitoring. The method involves setting hyperparameters for a model, grouping probe assemblies based on historical measurements, assigning unique IDs, selecting an optimization function, identifying a single probe assembly for monitoring, and sending thickness measurements for inspection. The probe assemblies include resistance temperature detectors and ultrasonic transducers for detecting corrosion. The method also validates measurements to distinguish between general and localized corrosion, down-selects probe assemblies during inspection, and utilizes optimization functions like median_TML_within_groupID.
Furthermore, the patent application details a system for detecting localized corrosion in components transporting materials over a distance. The system includes probe assemblies, a data store for historical measurements, a model trained on the data, and a monitoring apparatus. The apparatus groups probe assemblies, assigns unique IDs, selects optimization functions, identifies probe assemblies for monitoring, and outputs a list of identifiers. The system validates measurements, disregards unnecessary probe assemblies during inspection, and can monitor components like pipes and tanks. Hyperparameters like grouping_sensitivity and optimization functions such as minimum_average_TML_within_groupID are utilized. Additionally, a computer-readable medium stores instructions for down-selecting probe assemblies based on historical measurements, setting hyperparameters, training models, grouping probe assemblies, selecting optimization functions, identifying probe assemblies for monitoring, and sending measurements for inspection. During inspection, unnecessary probe assemblies are disregarded.
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