A barrier device remote fault intelligent diagnosis system and method

By using multi-cycle fusion diagnosis of multi-source sensor data, the current, angle and vibration data of the motor of the barrier gate equipment are collected, and the current deviation and vibration impact characteristics are extracted. This solves the problems of misjudgment and omission in the fault diagnosis of traditional barrier gate equipment, and realizes accurate fault identification and early warning.

CN121388898BActive Publication Date: 2026-07-24SHENZHEN WONSUN MASCH & ELECTRICAL TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHENZHEN WONSUN MASCH & ELECTRICAL TECH CO LTD
Filing Date
2025-12-25
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Traditional fault diagnosis methods for barrier gate equipment rely on a single signal source, which can easily lead to misjudgment or missed judgment, making it difficult to identify early faults or minor defects, thus affecting the accuracy of diagnosis and early warning capabilities.

Method used

The system collects motor current data, barrier arm angle data, and chassis vibration data of the barrier gate equipment. Through multi-cycle fusion diagnosis of multi-source sensor data, it extracts current deviation characteristics and vibration impact characteristics, jointly diagnoses fault types, and performs remote graded alarms.

Benefits of technology

It improves the accuracy of gate fault diagnosis, can identify sudden faults and early hidden dangers, and can provide accurate early warning of the severity and development stage of faults, significantly improving the accuracy and reliability of diagnostic conclusions.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a barrier gate device remote fault intelligent diagnosis system and method, extracts motor current amplitude sequences of each complete action cycle from motor current data of the barrier gate device, determines current deviation characteristics of the barrier gate device in a single complete action cycle according to all motor current amplitude sequences; extracts vibration effective value sequences of each complete action cycle from a machine case vibration data of the barrier gate device, determines vibration impact characteristics of the barrier gate device in a single complete action cycle according to each vibration effective value sequence; jointly diagnoses a current state of the barrier gate device through the current deviation characteristics and the vibration impact characteristics, outputs a fault type and a fault confidence of the barrier gate device, and when the fault confidence exceeds a confidence threshold of the barrier gate device, remotely classifies and alarms the barrier gate device based on the fault type. Based on the above scheme, multi-cycle fusion diagnosis of multi-source sensing data in the barrier gate device can be realized.
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Citation Information

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