Shenzhen, China

Xinan Wang

This inventor holds 1 USPTO granted patent. Top assignee: Shenzhen Technology University. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Xinan Wang. Retrieved from https://idiyas.com/inventor/xinan-wang-l42ic4hi

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Xinan Wang and Elevator Leveling Fault Detection.

Introduction

Xinan Wang is an inventor based in Shenzhen, China, associated with Shenzhen Technology University. His patent work addresses elevator safety and the reliable detection of leveling faults.

Latest Patents

Wang is associated with 1 patent: “Method and Apparatus for Determining Leveling Fault of Elevator.” The invention acquires an elevator’s leveling signal and target-floor signal, then compares the expected sequence of leveling-sensor signals with the sequence observed in real time as the elevator travels from a starting floor to the target floor. If the sequences match, the system determines that the elevator is leveling normally; if they differ, it identifies a leveling fault.

Career Highlights

Wang’s documented patent contribution focuses on applying signal-sequence comparison to elevator monitoring. This approach provides a method for identifying discrepancies between expected and actual leveling behavior.

Collaborations

Wang’s listed coworkers include Ruize Sun and Jianmin Cao. The available information does not specify their roles in the patent or their particular contributions.

Conclusion

Xinan Wang’s patent work at Shenzhen Technology University centers on detecting elevator leveling faults by comparing expected sensor signals with real-time measurements.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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