A. Saputra, H. Sofyan, T.E. Putra
The purpose of this research is to implement R software in developing a correlation between wavelet coefficient and fatigue life utilizing Fuzzy C-Means. The fatigue-based strain data were simulated at the range between 200 to 2000 µε through the application of constant and variable amplitudes with the mean values of negative, zero, and positive. The wavelet transforms involved were the 4th, 12th, 20th, and 30th orders of the continuous and discrete Daubechies wavelets as well as the Morlet wavelet. Meanwhile, the fatigue life was determined by Coffin-Manson, Morrow, and Smith-Watson-Topper models. R software with fclust package estimated 3 clusters as the optimum numbers with 1.5 as the fuzzifier value. Hereafter, the result showed that there was a negative correlation between the wavelet coefficient and fatigue life. The strongest correlation was between the 20th order of the discrete Daubechies wavelet and the Coffin-Manson model, i.e. −0.623 with the determination coefficient of 0.388. According to the results, it can be concluded that the software can be applied for clustering mechanical data. Therefore, it is recommended for mechanical engineering applications, involving complex and bigger data. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Department of Statistics, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia; Department of Mechanical Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
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