Wavelet-Based Optimization and Numerical Computing for Fault Detection Method—Signal Fault Localization and Classification Algorithm

محفوظ في:

التفاصيل البيبلوغرافية
الحاوية / القاعدة:	Algorithms vol. 18, no. 4 (2025), p. 217
المؤلف الرئيسي:	Sakovich Nikita
مؤلفون آخرون:	Aksenov Dmitry, Pleshakova Ekaterina, Gataullin Sergey
منشور في:	MDPI AG
الموضوعات:	Industrial equipment Accuracy Computation Classification Wavelet transforms Fault lines Fault location Optimization techniques Signal processing Error functions Adaptation Decomposition Numerical analysis Data analysis Localization Fault detection Numerical methods Data compression Wavelet analysis Internet of Things Seismic activity Machine learning Fourier transforms Fault diagnosis Failure analysis Structural integrity Neural networks Optimization Flexibility Algorithms Vibration analysis Methods
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الوصف
مستخلص:	This study focuses on the development of the WONC-FD (Wavelet-Based Optimization and Numerical Computing for Fault Detection) algorithm for the accurate detection and categorization of faults in signals using wavelet analysis augmented with numerical methods. Fault detection is a key problem in areas related to seismic activity analysis, vibration assessment of industrial equipment, structural integrity control, and electrical grid reliability. In the proposed methodology, wavelet transform serves to accurately localize anomalies in the data, and optimization techniques are introduced to refine the classification based on minimizing the error function. This not only improves the accuracy of fault identification but also provides a better understanding of its nature.
تدمد:	1999-4893
DOI:	10.3390/a18040217
المصدر:	Engineering Database