Sensing, identification, fault detection and diagnosis, and performance recovery of systems

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Wear, design flaws, and external influences and disturbances, such as overload, cause gradual deterioration in many systems, which can lead to inferior performance and/or catastrophic failure. Satisfactory control and monitoring of a system require accurate information about both the system and its individual components, and operational characteristics. Comprehensive information is often not readily available, particularly when the system is in operation. In addition, since equipment/machinery manufacturers do not generally foresee a need to determine and supply such information, they do not provide a built-in means to extract such data in the future. Over the past several years the applicant has been engaged in online system/parameter identification, fault detection, isolation and recovery. Systems modeling and simulation including such techniques as neural networks, fuzzy logic, genetic algorithms and wavelet analysis have been successfully explored and used.  Specific platforms (or fault cases) currently under study and of future interest are "knock", or the autoignition phenomenon in internal combustion engines, and actuator and sensor failure detection in spacecraft. In the case of knocks, in addition to causing inefficient operation and pollution, they also create pressures and forces above the design specifications, which could lead to mechanical damage and failure. We have successfully used wavelet transform, as a method of processing unsteady signals, in engine fault detection. We are proposing to develop complementary analysis tools to improve accuracy and the fault detection rate and extend the current results from single cylinder cases to more practical multi-cylinder applications. In the case of spacecraft actuator/senor failures, we are developing techniques for single and multiple component failures detection and devising schemes for system reconfiguration and recovery. We will examine new software/control and hardware redundancies with emphasis on optimal spatial placement of actuators and sensors in the spacecraft to improve the global first-level fail-safe characteristics of the system for robust recovery.