Authors: Francesca Forbicini, Nicolò Oreste Pinciroli Vago, Piero Fraternali

Published on: February 27, 2024

Impact Score: 7.6

Arxiv code: Arxiv:2402.17802

Summary

• What is new: This paper surveys recent research on Fault Detection, Fault Prediction, Forecasting, and Change Point Detection specifically for compressor-based machines, offering a comprehensive overview and classification of approaches not previously compiled together.
• Why this is important: The need for effective monitoring systems in compressor-based machines to detect faults, predict failures, forecast operations, and identify significant behavioural changes.
• What the research proposes: A survey and classification of the recent approaches and algorithms used for monitoring and predictive tasks in the operation of compressor-based machines.
• Results: Identification of gaps in current research and discussion on promising future directions for enhancing the reliability and efficiency of these machines.

Technical Details

Technological frameworks used: IoT connectivity, multivariate time series analysis

Models used: Fault Detection models, Fault Prediction models, Forecasting models, Change Point Detection models

Data used: Operational data from compressor-based machines

Potential Impact

Manufacturers and service providers in the refrigeration, HVAC, heat pump, and chiller industries could enhance product reliability and predictive maintenance services.

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