Study on Unified Chaotic System-Based Wind Turbine Blade Fault Diagnostic System

Abstract

At present, vibration signals are processed and analyzed mostly in the frequency domain. The spectrum clearly shows the signal structure and the specific characteristic frequency band is analyzed, but the number of calculations required is huge, resulting in delays. Therefore, this study uses the characteristics of a nonlinear system to load the complete vibration signal to the unified chaotic system, applying the dynamic error to analyze the wind turbine vibration signal, and adopting extenics theory for artificial intelligent fault diagnosis of the analysis signal. Hence, a fault diagnostor has been developed for wind turbine rotating blades. This study simulates three wind turbine blade states, namely stress rupture, screw loosening and blade loss, and validates the methods. The experimental results prove that the unified chaotic system used in this paper has a significant effect on vibration signal analysis. Thus, the operating conditions of wind turbines can be quickly known from this fault diagnostic system, and the maintenance schedule can be arranged before the faults worsen, making the management and implementation of wind turbines smoother, so as to reduce many unnecessary costs.

Soil Salinization Level Monitoring and Classifying by Mixed Chaotic Systems

“…Chih-Jer Lin et al adopted [47] the Chen-Lee chaotic system for analysis and took its chaotic attractor as the feature of the ball bearing malfunction recognition, the method combing Chen-Lee chaotic system, and BPNN (Back Propagation Neural Network) had a high identification rate and overall efficiency for the ball bearing malfunction. Ying-Che Kuo et al used [48] the unified chaotic system-based design to study the wind turbine blade fault diagnostic system, Lorenz system, the Lu system, and the Chen system was used to identify which one responds best to this system. The experimental results showed that the unified chaotic system had a significant effect on the vibration signal analysis.…”

Intelligent Ball Bearing Fault Diagnosis Using Fractional Lorenz Chaos Extension Detection

“…For signal analysis, both discrete Fourier [ 17 ] transform and wavelet [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ] were the most frequent analyses used. Over the last few years, chaos systems have been extensively used for diagnosis [ 25 , 26 ] with the fractional-order chaos method giving better diagnostic results, than a simpler chaotic system [ 27 , 28 ].…”