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In practical applications of wavelet transform, engineers and practitioners encounter challenges that arise due to the disparity between wavelet theory, which deals with continuous functions, and the digital nature of signals in engineering contexts. In particular, wavelet transform theory does not consider the effect of changes in digital signals on the result of the wavelet transform. This paper emphasizes the influence of the type of digital signals on the accuracy of wavelet transform in engineering applications and proposes an efficient wavelet function based on the derivative of the signal for better damage detection in beam structures. For this purpose, the obtained signals from the mode shapes of the steel beam are used to examine the efficiency of the proposed derivative-based wavelet transform. The effects of changes in boundary conditions, location of damage, and level of damage on the performance of the proposed method, are evaluated. Findings show that when we use the derivate of the signal in the wavelet transform, the location of damage in all damage scenarios is detected with high accuracy. This research demonstrates the importance of the type of signal used in the wavelet transform for enhancing the precision of fault and damage detection in signals. [ABSTRACT FROM AUTHOR]

This paper presents the effectiveness of a hybrid YUKI-RANDOM-FOREST, Particle Swarm Optimization-YUKI (PSO-YUKI), and balancing composite motion optimization algorithm (BCMO) based on artificial neural networks (ANN) for the best prediction of patch design considering the maximum principal stress. The study compares the maximum principal stress in a damaged pipe under different composite patch designs. Robust models have been developed and utilized in various applications. The research investigates the influence of cracks on the mechanical characteristics of API X70 steel in a test pipe under critical pressure. The numerical model employs the extended finite element method (XFEM) to simulate notches. Extending the optimization technique, the study examines the effect of crack presence in a pipeline section under internal pressure without and with composite repairs on the maximum principal stress. The sensitivity of stress is analyzed with respect to the design parameters of the composite patch. Finally, YUKI-RANDOM-FOREST, NN-PSO-YUKI, and NN-BCMO, with different parameters and hidden layer sizes are employed to predict the maximum principal stress under different composite patch designs, and yielding minimal error. Once the database was built, our model was prepared to predict various situations at the composite patch level. Compared to other methods, the obtained results with hybrid YUKI-RANDOM-FOREST are effective. The investigation technique is relevant to real-world engineering applications, structural safety control, and design processes. [ABSTRACT FROM AUTHOR]