tailieunhanh - Fuzzy Systems Part 7

Tham khảo tài liệu 'fuzzy systems part 7', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 6 A Hybrid Fuzzy System for Real-Time Machinery Health Condition Monitoring Wilson Wang Lakehead University Canada 1. Introduction Rotary machinery is widely used in various types of engineering systems ranging from simple electric fans to complex machinery systems such as aircraft. A reliable online condition monitoring system is very useful in industries both as a quality control scheme and as a maintenance tool. In quality control the early detection of faulty components can prevent machinery performance degradation and malfunction. As a maintenance tool machinery health condition monitoring enables the establishment of a maintenance program based on an early warning. This can be of great value in cases involving critical machines . airplanes power turbines and chemical engineering facilities where an unexpected shutdown can have serious economic or environmental consequences. Condition monitoring is an act of fault diagnosis by means of appropriate observations from different information carriers such as temperature acoustics lubricant or vibration. Vibration-based monitoring however is the most commonly used approach in industries because of its ease of measurement which also will be used in this study. Fault diagnosis is a sequential process involving two steps representative feature extraction and pattern classification. Feature extraction is a mapping process from the measured signal space to the feature space. Representative features associated with the health condition of a machinery component or subsystem are extracted by using appropriate signal processing techniques. Pattern classification is the process of classifying the characteristic features into different categories. The classical approach which is also widely used in industry relies on human expertise to relate the vibration features to the faults. This method however is tedious and not always reliable when the extracted features are contaminated by noise. Furthermore it is difficult for a .