| Judul | Sensing Technologies in Industrial Defect Detection / Peng Liu |
| Pengarang | Peng Liu |
| Penerbitan | 4052 Basel, Switzerland : MDPI, 2026 |
| Deskripsi Fisik | 222 :ill |
| ISBN | 978-3-7258-9210-5 |
| Subjek | Engineering; Quality control -- Optical methods |
| Catatan | "Summary This Reprint presents recent advances in sensing technologies for industrial defect detection and equipment condition assessment. The collected studies cover three closely connected stages of industrial sensing. The first focuses on acquiring reliable information from industrial components and processes through machine vision, infrared thermography, X-ray computed tomography, vibration sensing, and multisource monitoring. The second addresses the interpretation of sensing data through signal processing and machine learning for defect identification, fault diagnosis, and condition evaluation. The third extends sensing results toward prognostics and maintenance decision-making, including uncertainty-aware prediction and intelligent maintenance strategies. Together, these contributions demonstrate how industrial sensing is evolving from isolated inspection tasks toward integrated frameworks that connect data acquisition, condition understanding, and operational decision support. The Reprint also refl |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
https://www.mdpi.com/books/reprint/13538-sensing-technologies-in-industrial-defect-detection |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 449626192 | 670.427 Pen s | Baca Online | Perpustakaan Pusat - Online Resources Ebook |
Tersedia |
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| 005 | 20261024101051 | ||
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| 505 | # | # | $a "Summary This Reprint presents recent advances in sensing technologies for industrial defect detection and equipment condition assessment. The collected studies cover three closely connected stages of industrial sensing. The first focuses on acquiring reliable information from industrial components and processes through machine vision, infrared thermography, X-ray computed tomography, vibration sensing, and multisource monitoring. The second addresses the interpretation of sensing data through signal processing and machine learning for defect identification, fault diagnosis, and condition evaluation. The third extends sensing results toward prognostics and maintenance decision-making, including uncertainty-aware prediction and intelligent maintenance strategies. Together, these contributions demonstrate how industrial sensing is evolving from isolated inspection tasks toward integrated frameworks that connect data acquisition, condition understanding, and operational decision support. The Reprint also reflects several important challenges for practical deployment, including sensing robustness under changing operating conditions, limited and imbalanced industrial data, effective fusion of heterogeneous information, model generalization, interpretability, and uncertainty quantification. It provides a focused overview of current progress and emerging directions in intelligent industrial inspection, condition monitoring, and smart maintenance." |
| 650 | # | # | $a Engineering; Quality control -- Optical methods |
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