用开关声音检测道岔电机故障，实现远程自动化巡检。
Automatic Inspection Based on Switch Sounds of Electric Point Machines
- 通过麦克风采集道岔开关声，分析异常音频特征
- 2019年实验验证可实时发现转换错误，误报率低
- 适合铁路运维人员和智能监测系统开发者
自2018年起，东日本铁路公司与日立公司合作推进以物联网为基础的设备监测，旨在减少人工巡检工作量并实现精准预防性维护。传统电气特性监测难以替代视觉检查，且高性能传感器引入成本高。2019年，我们在“NS”型道岔电机中部署摄像头与麦克风，用于降低设备故障导致的停机时间，实现对锁闭部件状态的远程监控。提出一种基于声音信息检测道岔转换异常的方法，实验结果符合预期。该方法可实现设备故障的实时识别，显著减少人工视觉巡检需求。本文总结了自2019年起利用“开关声音”实现道岔电机自动化检测的技术研究成果。
原文摘要 · Abstract (English)
Since 2018, East Japan Railway Company and Hitachi, Ltd. have been working to replace human inspections with IoT-based monitoring. The purpose is Labor-saving required for equipment inspections and provide appropriate preventive maintenance. As an alternative to visual inspection, it has been difficult to substitute electrical characteristic monitoring, and the introduction of new high-performance sensors has been costly. In 2019, we implemented cameras and microphones in an ``NS'' electric point machines to reduce downtime from equipment failures, allowing for remote monitoring of lock-piece conditions. This method for detecting turnout switching errors based on sound information was proposed, and the expected test results were obtained. The proposed method will make it possible to detect equipment failures in real time, thereby reducing the need for visual inspections. This paper presents the results of our technical studies aimed at automating the inspection of electronic point machines using sound, specifically focusing on ``switch sound'' beginning in 2019.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。