Research on dewar temperature monitoring and fault prediction for receivers based on K-means++

<p indent="0mm">This paper achieves indirect monitoring and prediction of the working conditions of the refrigeration system by monitoring the temperature of the receiver Dewar, thereby ensuring that the radio telescope can maintain its optimal operating state continuously and thus guarantee its observational sensitivity. This goal is achieved by fully utilizing existing temperature monitoring data, without the need for additional hardware investment, thus reducing costs and enhancing practicality. By setting thresholds and identification factors, this paper employs the K-means++ clustering algorithm to process the temperature data of the receiver Dewar. The algorithm classifies the data into four categories, representing normal, temperature rise, temperature drop, and ambient temperature states. The results indicate that by monitoring the temperature characteristics of the receiver Dewar, this paper can conduct in-depth analysis of key information such as the refrigeration conditions of the receiver and the gas tightness of the Dewar container, thereby providing a solid basis for fault prediction and maintenance. Furthermore, the K-means++ algorithm exhibits good performance and applicability when processing such data, providing strong support for subsequent research and applications in this paper. This research finding is of great significance for improving the observational sensitivity and stability of radio telescopes.