# Automatic Inspection Based on Switch Sounds of Electric Point Machines

## TL;DR

This paper presents a method for automating the inspection of electric point machines by analyzing switch sounds, aiming to replace visual inspections with real-time, sound-based failure detection to improve maintenance efficiency.

## Contribution

The study introduces a novel sound-based inspection technique for electric point machines, demonstrating its potential for real-time failure detection and maintenance automation.

## Key findings

- Sound analysis can detect switching errors effectively.
- Real-time monitoring reduces inspection labor and downtime.
- Sound-based method complements existing inspection techniques.

## Abstract

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.