Rotating machines have been widely used in industrial engineering. The fault diagnosis of rotating machines plays a vital important role to reduce the catastrophic failures and heavy economic loss. However, the measured vibration signal of rotating machinery often represents non-linear and non-stationary characteristics, resulting in difficulty in the fault feature extraction. As a statistical measure, entropy can quantify the complexity and detect dynamic change through taking into account the non-linear behavior of time series. Therefore, entropy can be served as a promising tool to extract the dynamic characteristics of rotating machines. Recently, many studies have applied entropy in fault diagnosis of rotating machinery. This paper aims to investigate the applications of entropy for the fault characteristics extraction of rotating machines. First, various entropy methods are briefly introduced. Its foundation, application, and some improvements are described and discussed. The review is divided into eight parts: Shannon entropy, Renyi entropy, approximate entropy, sample entropy, fuzzy entropy, permutation entropy, and other entropy methods. In each part, we will review the applications using the original entropy method and the improved entropy methods, respectively. In the end, a summary and some research prospects are given.

The Entropy Algorithm and Its Variants in the Fault Diagnosis of Rotating Machinery: A Review

Fatigue reliability assessment of turbine discs under multi‐source uncertainties

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In order to present a new method for analyzing the reliability of a two-link flexible robot manipulator, Lagrange dynamics differential equations of the two-link flexible robot manipulator were established by using the integrated modal method and the multi-body system dynamics method. By using the Monte Carlo method, the random sample values of the dynamic parameters were obtained and Lagrange dynamics differential equations were solved for each random sample value which revealed their displacement, speed and acceleration. On this basis, dynamic stresses and deformations were obtained. By taking the maximum values of the stresses and the deformations as output responses and the random sample values of dynamic parameters as input quantities, extremum response surface functions were established. A number of random samples were then obtained by using the Monte Carlo method and then the reliability was analyzed by using the extremum response surface method. The results show that the extremum response surface method is an efficient and fast reliability analysis method with high-accuracy for the two-link flexible robot manipulator.

Guang-Chen Bai

Papers

Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes

Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression

Extremum response surface method of reliability analysis on two-link flexible robot manipulator

Reliability-based low-cycle fatigue damage analysis for turbine blade with thermo-structural interaction

Dynamic surrogate modeling approach for probabilistic creep-fatigue life evaluation of turbine disks