遇见数据集

Dataset for Sound-based Anomalies Detection in Agricultural Robotics Application

收藏
Zenodo2023-04-06 更新2026-05-25 收录
数据链接:
官方服务:

资源简介:

This data set contains data related to a Mowing Intelligent Tool (MowIT). Two different microphones were used to collect the sound samples, recording the audio with just one single channel, with a sampling rate of 44100 Hz and 16 bits resolution. The data provided by an inertial measurement unit (IMU) was also recorded since that was already integrated into the MowIT. Two different data collections were performed in different open-air environments with grass to cut. In each collection, eight different sample sets were made, five with the machine cutting using a trimmer line and the other three using the blades. Various combinations were used in each set, and tools were or were not placed on each of the three cutting axes of the MowIT. For each group, the acquisitions were designated from 0 to 7. Each folder of the first collection is a combination containing two audio files, one for each microphone used, the IMU data and a photograph of the lower part of the MowIT to understand the configuration used. In the second collection, to improve the variety of data, three distinct sub-sets were performed for combination: the first with the MowIT turned on but not cutting grass and the next two cutting grass. In samples 4 and 7, there is one audio where the MowIT cuts but stops due to motor stress. In sample 6, the initial recording was not made without cutting grass, and only the two recordings were made cutting grass.

本数据集包含与割草智能工具(Mowing Intelligent Tool,MowIT)相关的各类数据。本次采集使用两款不同麦克风采集声音样本,采用单声道录制音频,采样率为44100Hz,位深为16比特。同时同步记录了集成于该工具的惯性测量单元(IMU)数据。 两次数据采集作业分别在两处不同的露天草地环境中开展。单次采集中共生成8组不同样本集:其中5组采用割绳模式进行割草作业,剩余3组采用刀片模式进行割草。每组样本均设置了多种组合工况,并在MowIT的三个切割轴上分别安装或不安装工具,每组采集样本以0至7进行编号。 第一次采集的每个文件夹均包含一套完整数据:对应两款麦克风的音频文件各1份、惯性测量单元数据,以及一张MowIT下部的实拍照片,用于说明本次采集所用的配置方案。 为提升数据多样性,第二次采集新增了三种独立的子工况组合:第一种为MowIT开机但未执行割草作业,后两种为割草作业工况。在样本4与样本7中,存在一段MowIT因电机过载停机前的割草音频。样本6未采集无割草作业的初始音频,仅包含两段割草作业的录音。

提供机构:
Zenodo
创建时间:
2022-10-13
二维码
社区交流群
二维码
科研交流群
商业服务