Опубликована: Окт. 31, 2024
Язык: Английский
Опубликована: Окт. 31, 2024
Язык: Английский
Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126399 - 126399
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126439 - 126439
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
1Physics of Fluids, Год журнала: 2024, Номер 36(12)
Опубликована: Дек. 1, 2024
Gas outbursts in coal seams represent a severe and formidable hazard, posing significant threat to the safety of mining operations. The advanced early warning is crucial preventive measure against outbursts. Acoustic emission (AE) electromagnetic radiation (EMR) are monitoring techniques for gas However, during operations, interference signals from AE EMR may arise. Due impact these signals, use statistical indicators time-frequency feature analysis lead false alarms missed detections outburst warnings. advancement deep learning offers new methods intelligent identification risks. This article proposes an method detecting precursor conducting comprehensive index based on EMR. First, reconstruct signal using wavelet packet decomposition then process resulting with diffusion-semi-supervised classification algorithm, employing partially labeled train model risk By analyzing prominent EMR, establish Bayesian networks, thereby achieving findings suggest that question, which employs training dataset comprising 60% manually annotated data, proficient precisely identifying adept at range signals. It provides basis distinguished multi-level warning. research outcomes significantly enhance reliability offering effective seams, power manifestations, abnormal gas.
Язык: Английский
Процитировано
3Advanced Engineering Informatics, Год журнала: 2025, Номер 65, С. 103189 - 103189
Опубликована: Фев. 15, 2025
Язык: Английский
Процитировано
0Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113389 - 113389
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0Applied Soft Computing, Год журнала: 2025, Номер unknown, С. 113172 - 113172
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 155, С. 111099 - 111099
Опубликована: Май 12, 2025
Язык: Английский
Процитировано
0Control Engineering Practice, Год журнала: 2025, Номер 162, С. 106391 - 106391
Опубликована: Май 13, 2025
Язык: Английский
Процитировано
0IEEE Sensors Journal, Год журнала: 2024, Номер 25(1), С. 1076 - 1085
Опубликована: Ноя. 14, 2024
Язык: Английский
Процитировано
1Journal of Marine Science and Engineering, Год журнала: 2024, Номер 12(10), С. 1792 - 1792
Опубликована: Окт. 9, 2024
The application of artificial intelligence models for the fault diagnosis marine machinery increased expeditiously within shipping industry. This relates to effectiveness in capturing patterns systems that are becoming more complex and where traditional methods is unfeasible. However, despite these advances, lack labelling data still a major concern due confidentiality issues, appropriate data, instance. In this study, method based on histogram similarity hierarchical clustering proposed as an attempt label distinct anomalies faults occur dataset so supervised learning can then be implemented. To validate methodology, case study main engine tanker vessel considered. results indicate preliminary option classify types may appear dataset, model achieved accuracy approximately 95% presented.
Язык: Английский
Процитировано
0