Reliability Analysis and Fault Diagnosis Model of Agricultural Irrigation System Based on NB-IoT

With the development of Internet of Things technology, especially the application of NB-IoT technology in agriculture, the traditional agricultural irrigation method is gradually transforming to intelligence. In this paper, an agricultural irrigation system based on NB-IoT technology is proposed. The system can realize accurate irrigation and improve water resources utilization efficiency by monitoring farmland environmental parameters in real time and transmitting data to cloud server for processing and analysis. The system architecture includes perception layer, network layer and application layer, which work together to realize real-time monitoring of farmland environment, data transmission and intelligent irrigation control. This paper focuses on the reliability analysis and fault diagnosis model of the system, evaluates the system reliability through fault tree analysis (FTA), and constructs a machine learning model combined with random forest (RF) algorithm for fault diagnosis. The experimental results show that the system can effectively identify and classify faults, with an accuracy rate of 95 % and 92 % on the verification set, and successfully locate the actual faults. The research in this paper is of great significance for promoting agricultural modernization, improving water resources utilization efficiency and reducing production costs.