A multi-modal liquid level monitoring method and system based on time sequence feature analysis

By using multi-dimensional liquid level compensation and time-series characteristic analysis, the problems of inaccurate liquid level monitoring and insufficient RO membrane health assessment in water purification equipment have been solved, achieving high-precision liquid level monitoring and autonomous anomaly handling, thereby improving equipment operation stability and management efficiency.

CN121167204BActive Publication Date: 2026-04-17HANGZHOU WISENS TECH CO LTD
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Patent Information

Application Number
CN202511368020.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-09-24
Publication Date
2026-04-17
Estimated Expiration
2045-09-24

AI Technical Summary

Technical Problem

In existing water purification and storage equipment, liquid level monitoring is inaccurate, sensor aging and environmental changes lead to large measurement errors, RO membrane health assessment lacks systematic methods, and equipment malfunctions result in delayed response requiring manual intervention, increasing costs and risks.

Method used

By employing a multi-dimensional liquid level compensation method, and through time-series feature analysis, combined with sensor data preprocessing, fluid static pressure formula, and anomaly type determination, autonomous control commands are generated to achieve high-precision liquid level monitoring and RO membrane health assessment.

Benefits of technology

Improve the accuracy of liquid level measurement, reduce equipment misjudgment, accurately assess the health of RO membranes, reduce the frequency of manual intervention, and improve equipment stability and management efficiency.

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Abstract

This invention relates to the field of water purification equipment monitoring technology, and particularly to a multimodal liquid level monitoring method and system based on time-series feature analysis. The method includes: collecting and preprocessing multi-dimensional data through sensors to obtain the original pressure value, real-time water temperature value, real-time TDS value, and current operating condition indicator after interference removal; inputting the original pressure value and water density basic parameters into the hydrostatic pressure formula to obtain the initial liquid level value; combining the real-time water temperature value, real-time liquid level fluctuation frequency, and reference fluctuation frequency to obtain the final high-precision liquid level value; based on the final high-precision liquid level value, real-time TDS value, inlet water pressure data, and current operating condition indicator, calculating the flow rate attenuation score, TDS stability score, and correlation score according to weighted and threshold rules, and combining the three scores to obtain the overall health score; calculating the liquid level change rate and comparing it with a standard range, determining and outputting the anomaly type, and generating control commands. This solution improves the accuracy of liquid level measurement through multi-dimensional liquid level compensation.
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