Integrated Condition Monitoring and Prognosis Method for Incipient Defect Detection and Remaining Life Prediction of Low Speed Slew Bearings

Abstract

This paper presents an application of multivariate state estimation technique (MSET), sequential probability ratio test (SPRT) and kernel regression for low speed slew bearing condition monitoring and prognosis. The method is applied in two steps.Step (1) is the detection of the incipient slew bearing defect. In this step, combined MSET and SPRT is used with circular-domain kurtosis, time-domain kurtosis, wavelet decomposition (WD) kurtosis, empirical mode decomposition (EMD) kurtosis and the largest Lyapunov exponent (LLE) feature.Step (2) is the prediction of the selected features' trends and the estimation of the remaining useful life (RUL) of the slew bearing. In this step, kernel regression is used with time-domain kurtosis, WD kurtosis and the LLE feature. The application of the method is demonstrated with laboratory slew bearing acceleration data.

Wavelet Packets Transform processing and Genetic Neuro-Fuzzy classification to detect faulty bearings

“…In the third layer, the defuzzification process is achieved and the global system output is reached by equation (6). N 3 represents the GNF output number; in this work, there are two outputs, and each one is the estimated value of kth output given by jth node…”

“…As a result, condition monitoring allows for the detection of incipient faulty mechanical elements, which is why this method is such a widely explored research field. [1][2][3][4][5][6][7][8] An important aspect of this work is that the experimental laboratory bench used to collect data includes a radial load due to the fact that this is the most important force for which rolling bearings are designed.…”

Introduction to Special Issue on Symmetry in Mechanical Engineering

“…The presented solutions, methods, and approaches can be improved and used in the future. Moreover, mechanical engineering is essential for fault diagnosis of machines [10][11][12][13][14][15][16][17][18][19][20][21][22] and the analysis of temperature [23][24][25]. The mechanical properties of materials are also investigated in the literature [26][27][28].…”

Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components

“…In recent years, bearing monitoring has received considerable attention due to the criticality of bearings faults [22,[45][46][47][48][49][50]. In particular, some works proposed in the literature have already modeled the degradation of bearings as a hidden process.…”