Machine Health Monitoring and Fault Diagnosis Techniques (Volume II)
This Special Issue brings together groundbreaking research focused on the enhancement of fault diagnosis and condition monitoring across various mechanical and electrical systems, leveraging advanced sensor technologies and intelligent diagnostic methods. The contributions encompass innovative appro...
में बचाया:
| स्वरूप: | Online |
|---|---|
| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| विषय: | |
| ऑनलाइन पहुंच: | ONIX_20250220_9783725827237_402 |
| टैग: |
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!
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| _version_ | 1869524456461828096 |
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| collection | Directory of Open Access Books |
| description | This Special Issue brings together groundbreaking research focused on the enhancement of fault diagnosis and condition monitoring across various mechanical and electrical systems, leveraging advanced sensor technologies and intelligent diagnostic methods. The contributions encompass innovative approaches such as deep learning models for transformer and rolling bearing fault detection using vibration signals and time–frequency analyses, significantly boosting diagnostic accuracy and robustness. This collection also explores cutting-edge methodologies like Bayesian-optimized machine learning techniques and the application of vision transformers and convolutional neural networks to manage complex fault scenarios. With a strong emphasis on cross-domain diagnostics, the articles provide insight into the adaptive models capable of maintaining their performance across different operational conditions, enhancing real-time monitoring capabilities. This Special Issue is an essential resource for professionals and researchers dedicated to developing resilient and efficient solutions for equipment reliability, operational safety, and predictive maintenance. The collection reflects the forefront of sensor-based condition monitoring, fostering advances that support the sustainable and safe operation of critical systems. |
| format | Online |
| id | doab-20.500.12854ir-153038 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1530382025-02-20T13:27:57Z Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) Sun, Shilong Shen, Changqing Wang, Dong Machine health monitoring Fault diagnosis Intelligent diagnosis algorithm. thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology This Special Issue brings together groundbreaking research focused on the enhancement of fault diagnosis and condition monitoring across various mechanical and electrical systems, leveraging advanced sensor technologies and intelligent diagnostic methods. The contributions encompass innovative approaches such as deep learning models for transformer and rolling bearing fault detection using vibration signals and time–frequency analyses, significantly boosting diagnostic accuracy and robustness. This collection also explores cutting-edge methodologies like Bayesian-optimized machine learning techniques and the application of vision transformers and convolutional neural networks to manage complex fault scenarios. With a strong emphasis on cross-domain diagnostics, the articles provide insight into the adaptive models capable of maintaining their performance across different operational conditions, enhancing real-time monitoring capabilities. This Special Issue is an essential resource for professionals and researchers dedicated to developing resilient and efficient solutions for equipment reliability, operational safety, and predictive maintenance. The collection reflects the forefront of sensor-based condition monitoring, fostering advances that support the sustainable and safe operation of critical systems. 2025-02-20T13:27:55Z 2025-02-20T13:27:55Z 2024 book ONIX_20250220_9783725827237_402 9783725827237 9783725827244 https://directory.doabooks.org/handle/20.500.12854/153038 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10234 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2724-4 10.3390/books978-3-7258-2724-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725827237 9783725827244 204 Basel open access |
| spellingShingle | Machine health monitoring Fault diagnosis Intelligent diagnosis algorithm. thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title | Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title_full | Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title_fullStr | Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title_full_unstemmed | Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title_short | Machine Health Monitoring and Fault Diagnosis Techniques (Volume II) |
| title_sort | machine health monitoring and fault diagnosis techniques volume ii |
| topic | Machine health monitoring Fault diagnosis Intelligent diagnosis algorithm. thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| topic_facet | Machine health monitoring Fault diagnosis Intelligent diagnosis algorithm. thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| url | ONIX_20250220_9783725827237_402 |