Growing Structure Multiple Model Systems for Anomaly Detection and Fault Diagnosis
نویسندگان
چکیده
A new anomaly detection scheme based on growing structure multiple model system (GSMMS) is proposed in this paper to detect and quantify the effects of anomalies. The GSMMS algorithm combines the advantages of growing self-organizing networks with efficient local model parameter estimation into an integrated framework for modeling and identification of general nonlinear dynamic systems. The identified model then serves as a foundation for building an effective anomaly detection and fault diagnosis system. By utilizing the information about system operation region provided by the GSMMS, the residual errors can be analyzed locally within each operation region. This local decision making scheme can accommodate for unequally distributed residual errors across different operational regions. The performance of the newly proposed method is evaluated through anomaly detection and quantification in an electronically controlled throttle system, which is simulated using a high-fidelity engine simulation software package provided by a major automotive manufacturer for control system development. DOI: 10.1115/1.3155004
منابع مشابه
Online Fault Detection and Isolation Method Based on Belief Rule Base for Industrial Gas Turbines
Real time and accurate fault detection has attracted an increasing attention with a growing demand for higher operational efficiency and safety of industrial gas turbines as complex engineering systems. Current methods based on condition monitoring data have drawbacks in using both expert knowledge and quantitative information for detecting faults. On account of this reason, this paper proposes...
متن کاملVariable Speed Wind Turbine DFIG Back to Back Converters Open-Circuit Fault Diagnosis by Using of Combiniation Signal-Based and Model-Based Methodes
Condition monitoring (CM) and Fault Detection (FD) of wind turbine lead to increase in reliability and availability of turbine. IGBT open circuit of wind turbine converter will bring about depletion in output current of converter and as a result, reduction in production of wind turbine power. In this research, back to back converter IGBT open - gate fault for wind turbine based on DFIG is detec...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کاملOn the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model
This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...
متن کاملDesign of nonlinear parity approach to fault detection and identification based on Takagi-Sugeno fuzzy model and unknown input observer in nonlinear systems
In this study, a novel fault detection scheme is developed for a class of nonlinear system in the presence of sensor noise. A nonlinear Takagi-Sugeno fuzzy model is implemented to create multiple models. While the T-S fuzzy model is used for only the nonlinear distribution matrix of the fault and measurement signals, a larger category of nonlinear systems is considered. Next, a mapping to decou...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009