Maintaining thermal balanceThermal balance in aluminum electrolysis cellsAluminum electrolysis cell is essential for operational stability, energy efficiencyEnergy efficiency, and process longevity. This balance is affected by thermal events from normal operations and anomalies such as anode effectsAnode Effect (AE). A key indicator is the spatial and temporal evolution of the ledge which is highly sensitive to thermal fluctuations. While previous studies focused on shell temperatureShell temperature and ledge tracking, few have addressed characterizationCharacterization and detection of thermal events. This study aims to characterize thermocouple signals associated with thermal events, particularly anode changesAnode change. Using a combination of signal processingProcessing and machine learningMachine learning, specifically k-means clusteringClustering, distinct thermal patterns were identified. Data were collected from a fully instrumented industrial cell and processed through feature extractionExtraction and selection. The findings were validated by an analog model and a full-scale industrial cell. This method demonstrated reliable pattern recognition and opens new avenues for process controlProcess control, predictive maintenance, and operational efficiencyOperational efficiency.