Intelligent bladeless fan environment monitoring system

By combining a multi-source sensor network and an edge AI processor, the sensor drift and data delay problems of the bladeless fan environmental monitoring system in salt fog and humid heat environments are solved, millisecond-level fault diagnosis and predictive maintenance are achieved, and the reliability and adaptability of the system are improved.

CN120685152APending Publication Date: 2025-09-23XUANTIE WIND ENERGY (SHENZHEN) TECH CO LTD
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Patent Information

Application Number
CN202510798594.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-16
Publication Date
2025-09-23

AI Technical Summary

Technical Problem

The environmental monitoring system of bladeless fans is easily affected by salt spray, humidity and heat at the hardware level. Sensors drift severely and lack a self-calibration mechanism. Data processing delays lead to low fault diagnosis accuracy, making it difficult for system integration to cover new failure modes. Predictive maintenance capabilities are insufficient, and the localization rate of equipment is low, resulting in high costs for integrating heterogeneous systems.

Method used

By adopting a multi-source sensor network, edge AI processor and self-correcting algorithm, combined with wind power-battery dual power supply and wireless relay technology, a low-cost, highly reliable integrated monitoring system is built to achieve millisecond-level fault diagnosis and predictive maintenance.

Benefits of technology

It significantly improves fault response accuracy and operation and maintenance efficiency, reduces calibration frequency and construction costs, overcomes monitoring blind spots and prediction bottlenecks of bladeless fans in extreme environments, and improves the localization rate of equipment and the adaptability of the system.

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Abstract

The invention relates to the technical field of bladeless fans, in particular to an intelligent bladeless fan environment monitoring system which comprises a multi-source sensor network module, an edge calculation processing module, a dual-mode power supply module, a wireless communication module and an intelligent monitoring module. The multi-source sensor network module comprises at least 10 paths of dry contact input interfaces, a temperature and humidity sensor interface, a water immersion detection interface and a displacement monitoring interface; compared with the defects that the prior art depends on a single threshold value alarm mechanism, the missing report rate is high, and composite faults cannot be recognized, the scheme adopts a millisecond-level three-level alarm system, multi-dimensional data such as a vibration spectrum and a temperature gradient are diagnosed in real time through edge AI, a dynamic priority work order distribution mechanism is combined, and the reliability of the system is improved. The fault response accuracy and the operation and maintenance efficiency are remarkably improved, and the crossing from passive alarm to active intervention is realized.
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