Temporal-Aware Chain-of-Thought Reasoning for Vibration-Based Pump Fault Diagnosis
সংরক্ষণ করুন:
| প্রকাশিত: | Processes vol. 13, no. 8 (2025), p. 2624-2647 |
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| প্রধান লেখক: | |
| অন্যান্য লেখক: | , , |
| প্রকাশিত: |
MDPI AG
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| ট্যাগগুলো: |
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| সার সংক্ষেপ: | Industrial pump systems require real-time fault diagnosis for predictive maintenance, but conventional Chain-of-Thought (COT) reasoning faces computational bottlenecks when processing high-frequency vibration data. This paper proposes Vibration-Aware COT (VA-COT), a novel framework that integrates multi-domain feature fusion (time, frequency, time–frequency) with adaptive reasoning depth control. Key innovations involve expert prior-guided dynamic feature selection to optimize edge-device inputs, complexity-aware reasoning chains reducing computational steps by 40–65% through confidence-based early termination, and lightweight deployment on industrial ARM-based single-board computers (SBCs). Evaluated on a 12-class pump fault dataset (5400 samples from centrifugal/gear pumps), VA-COT achieves 93.2% accuracy surpassing standard COT (89.3%) and CNN–LSTM (Convolutional Neural Network-Long Short-Term Memory network) (91.2%), while cutting latency to <1.1 s and memory usage by 65%. Six-month validation at pump manufacturing facilities demonstrated 35% maintenance cost reduction and 98% faster diagnostics versus manual methods, proving its viability for IIoT (Industrial Internet of Things) deployment. |
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| আইএসএসএন: | 2227-9717 |
| ডিওআই: | 10.3390/pr13082624 |
| সম্পদ: | Materials Science Database |