Rotating blade faults classification of a rotor-disk-blade system using artificial neural network

Abstract

<span lang="EN-US">In this paper, the artificial neural network (ANN) has been utilized for rotating machinery faults detection and classification. First, experiments were performed to measure the lateral vibration signals of laboratory test rigs for rotor-disk-blade when the blades are defective. A rotor-disk-blade system with 6 regular blades and 5 blades with various defects was constructed. Second, the ANN was applied to classify the different </span><em><span lang="EN-US">x</span></em><span lang="EN-US">- and </span><em><span lang="EN-US">y</span></em><span lang="EN-US">-axis lateral vibrations due to different blade faults. The results based on training and testing with different data samples of the fault types indicate that the ANN is robust and can effectively identify and distinguish different blade faults caused by lateral vibrations in a rotor. As compared to the literature, the present paper presents a novel work of identifying and classifying various rotating blade faults commonly encountered in rotating machines using ANN. Experimental data of lateral vibrations of the rotor-disk-blade system in both </span><em><span lang="EN-US">x</span></em><span lang="EN-US">- and </span><em><span lang="EN-US">y</span></em><span lang="EN-US">-directions are used for the training and testing of the network.</span>

Application of multilayer perceptron to deep reinforcement learning for stock market trading and analysis

“…We pick the best performing specialist with most note value sharpe proportion. The Sharpe proportion [19] more prominent than 1.0 is viewed as great. The Sharpe proportion is, 𝑆ℎ𝑎𝑟𝑝𝑒 𝑅𝑎𝑡𝑖𝑜 = 𝑅 𝑝 −𝑅 𝑓 𝜎 𝑝 (5) where 𝑅 𝑝 = return of portfolio, 𝑅 𝑓 = risk-free rate, and 𝜎 𝑝 = standard deviation of portfolio's excess return.…”

“…The novel feature extraction method was developed for improving the classification performance of the remotely sensed data using SL [18]. Using back propagation algorithm [19], MLP-ANN [20] and extreme learning machine (ELM) [21], the fault detection and classification method was developed for rotating machinery. The butterfly optimization algorithm utilizing the Levy flight (BOALF) and modified butterfly optimization algorithm (BOARN) was proposed for detecting the pneumonia diseases [22].…”