Artificial Intelligence in Fault Diagnosis and Signal Processing
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The aim of this reprint is to immerse the reader in the latest technological approaches employed in the detection and diagnosis of faults in industrial processes. As the early detection of faults avoids damage that may be irreparable to machinery, reducing the performance of the control system and reducing the process efficiency, which would result in a decrease in production, new approaches to the detection and diagnosis of faults have become a compulsory task in any Industry 4.0 implementation. To develop such a new generation of fault detection systems, the use of artificial intelligence te...
The aim of this reprint is to immerse the reader in the latest technological approaches employed in the detection and diagnosis of faults in industrial processes. As the early detection of faults avoids damage that may be irreparable to machinery, reducing the performance of the control system and reducing the process efficiency, which would result in a decrease in production, new approaches to the detection and diagnosis of faults have become a compulsory task in any Industry 4.0 implementation. To develop such a new generation of fault detection systems, the use of artificial intelligence techniques and advanced solutions in signal processing have also become the most suitable approach. The result of this issue is a collection of 15 works highlighting the latest advances in this topic, bringing researchers and industrial practitioners together to share their findings and present ideas that are relevant in the field of fault diagnosis using artificial intelligence and signal processing.
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