FORECASTING AND ANOMALY DETECTION METHOD FOR LOW DENSITY POLYETHYLENE AUTOCLAVE REACTOR

The present invention relates to a forecasting method for a low-density polyethylene autoclave reactor that enables future estimation and detection of anomalies by generating deep learning models with real-time sensor data in a low density polyethylene autoclave reactor.

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Bibliographic Details
Main Authors EZDESIR, Ayhan, KUCUK, Ali, YURTSEVEN, Merve, ALPASLAN, Ferda Nur, ISYAPAR, Muhammet Tugberk, UNER, Deniz, INAN, Muhammed
Format Patent
LanguageEnglish
French
German
Published 05.07.2023
Subjects
CALCULATING
CHEMISTRY
COMPOSITIONS BASED THEREON
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROL OR REGULATING SYSTEMS IN GENERAL
CONTROLLING
COUNTING
FUNCTIONAL ELEMENTS OF SUCH SYSTEMS
MACROMOLECULAR COMPOUNDS OBTAINED BY REACTIONS ONLY INVOLVINGCARBON-TO-CARBON UNSATURATED BONDS
METALLURGY
MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS
ORGANIC MACROMOLECULAR COMPOUNDS
PHYSICS
REGULATING
THEIR PREPARATION OR CHEMICAL WORKING-UP
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Summary:The present invention relates to a forecasting method for a low-density polyethylene autoclave reactor that enables future estimation and detection of anomalies by generating deep learning models with real-time sensor data in a low density polyethylene autoclave reactor.
Bibliography:Application Number: EP20210218047