Abnormity diagnosis and adaptive control method and system for irrigation valve

By acquiring data from multiple sensors in real time and analyzing the pattern recognition model, precise location and adaptive control of irrigation valve faults were achieved, solving the problems of inaccurate fault location and low maintenance efficiency in traditional technologies, and improving the stability and efficiency of the irrigation system.

CN121058542APending Publication Date: 2025-12-05GUANGZHOU SHANJI IOT TECH CO LTD
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Patent Information

Application Number
CN202511213310.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-08-28
Publication Date
2025-12-05

AI Technical Summary

Technical Problem

Existing irrigation valve monitoring technology cannot accurately locate and differentiate faults, nor can it implement differentiated recovery strategies based on specific fault types, resulting in low maintenance efficiency and difficulty in ensuring the continuous and efficient operation of the irrigation system.

Method used

By acquiring multi-source sensor data from irrigation valves in real time, performing time synchronization processing and pattern recognition model analysis, and combining sensor time-series data and environmental data, accurate fault location and adaptive control can be achieved.

Benefits of technology

It enables precise location and autonomous repair of irrigation valve malfunctions, improves detection sensitivity and response efficiency, reduces manual intervention costs, and ensures the continuous and stable operation of the irrigation system.

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Abstract

The invention relates to the field of intelligent irrigation, in particular to an abnormal diagnosis and self-adaptive control method and system for an irrigation valve, and the method comprises the steps: obtaining the data of a multi-source sensor of the irrigation valve in real time; analyzing the multi-source sensor data to obtain a plurality of irrigation valve parameters, and performing time synchronization processing on each irrigation valve parameter to form sensor time sequence data; inputting the time sequence data of the sensor into a preset mode recognition model, performing real-time analysis through the preset mode recognition model, and outputting an analysis result; when the analysis result is that the data are abnormal, an abnormal alarm is triggered, and abnormal positioning information is output; in response to the abnormal alarm, acquiring environment data corresponding to the abnormal positioning information, fusing the sensor time sequence data, the abnormal positioning information and the environment data, and determining a fault type; and on the basis of the fault type, irrigation valve adjustment parameters and a self-adaptive regulation and control strategy are generated. Autonomous adjustment and fault recovery of the system are achieved, manual intervention cost is reduced, and continuous and stable operation of the irrigation system is guaranteed.
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