FE-DGCAN DataSet 候选 · 未审核

doi:10.21227/ntry-z103

"This dataset is designed for the task of mechanical anomaly sound detection. It consists of audio recordings in .wav format, each with a duration of 10 seconds. The dataset is divided into two subsets: The recordings include various types of mechanical operation sounds, encompassing both normal and abnormal conditions. This dataset provides a reliable benchmark for developing and assessing machine learning models aimed at detecting and classifying anomalous mechanical sounds, thereby contributing to the advancement of intelligent fault diagnosis and predictive maintenance systems."

落地页
https://ieee-dataport.org/documents/fe-dgcan-dataset
许可证
CC-BY-4.0 (判读置信:inferred)
国内可访问性
国内直连:可达 (2026-07-11 检测) 代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。
PHM 任务
anomaly_detection fault_diagnosis

故障工况

fault_type: healthy_baseline
溯源(PROV,5 条)
source_url: https://ieee-dataport.org/documents/fe-dgcan-datasetsource_citation: quarry_mining_pool datacite#10.21227/ntry-z103retrieved_on: 2026-07-09asserted_by: automated_harvestnote: 反向挖掘 v3(KLS-018,词表圈选+全量人工复核):level=L1 score=0.65;候选区,晋升需人工核验
about_field: fault_conditionssource_citation: graphrag 抽取自论文 doi:10.21227/ntry-z103(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: healthy_baseline;候选区,晋升需人工核验(ADR-26)
about_field: taskssource_citation: graphrag 抽取自论文 doi:10.21227/ntry-z103(model=glm-5.2, temperature=0)retrieved_on: 2026-07-10asserted_by: automated_extractionconfidence_level: grounded_nativenote: values: anomaly_detection, fault_diagnosis;候选区,晋升需人工核验(ADR-26)
about_field: china_accessibilitysource_citation: KLS-009 链接健康扫描(lychee 双通道)retrieved_on: 2026-07-11asserted_by: automated_harvestnote: 定期刷新标注,仅覆盖本字段;历史结果以最新扫描为准
about_field: notessource_citation: 人工核验:zfbin(委托批次 KLS-033-B,2026-07-15)retrieved_on: 2026-07-15asserted_by: human_curatorconfidence_level: human_verifiednote: 人工改写。KLS-033 批次 B 维持判读注记