This paper describes a case study of model-based diagnostics system development for a space launch vehicle application. The diagnostics algorithms described in the paper can work with on-board or telemetry flight data. The key innovation is in designing a distributed diagnostics system that directly uses parametric data, such as sensors data. The computations are partitioned between the subsyst...

Induction motors are usually considered as one of the key components in various applications. To maintain the availability of induction motors, it calls for a reliable condition monitoring and prognostics strategy. Among the common induction motor faults, stator winding faults are usually diagnosed with current and voltage signals. However, if the same performance can be achieved, the use of vi...

There have been many studies on observer-based fault detection and isolation (FDI), such as using unknown input observer and generalized observer. Most of them require a nominal mathematical model of the system. Unlike sensor faults, actuator faults and process faults greatly affect the system dynamics. This paper presents a new process fault diagnosis technique without exact knowledge of the p...

Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. The technology of artificial neural networks has been successfully used to solve the motor incipient fault detection problem. The characteristics, obtained by this technique, distinguish them from the traditional ones, which, in most cases, need that the machine which...

The development of on line model-based fault detection systems in machinery improves the operational reliability of industrial systems and reduces the operational and maintenance costs. In this direction, this paper presents the use of modelling information to determine changes in characteristics from measured data for the fault detection purpose of hydraulic driven machines as well as for the ...

Corresponding author: Honeywell CA35, 1 Results Way, Cupertino, CA 95014; e-fax: (208) 545-6408; e-mail: [email protected], [email protected], Abstract. This paper describes a case study of modelbased diagnostics system development for an aircraft Auxiliary Power Unit (APU) turbine system. The offline diagnostics algorithms described in the paper work with historical data of a ...

A model based fault detection and diagnosis technique for DC motor is proposed in this paper. Fault detection using Kalman filter and its different variants are compared. Only incipient faults are considered for the study. The Kalman Filter iterations and all the related computations required for fault detection and fault confirmation are presented. A second order linear state space model of DC...

In this paper a hierarchical structure of several artificial neural networks has been developed for fault isolation purposes. Two different approaches have been considered. The hierarchical structure is the same for both approaches, but one uses multi-layer feedforward artificial neural networks and the other uses fuzzy neural networks. A result comparison between the two architectures will be ...

Condition monitoring is an important issue in the maintenance of electrical machines. In the last years many methods of fault detection were cited in literature. Most of the newly proposed advanced methods are for on-line and non-invasive monitoring. This means that the faults can be detected already in their incipient phase during the usual work of the monitored machines. The aims of this pape...

SENSOR DATA VALIDATION A.N. Boudaoud, M.H. Masson Heudiasyc, U.M.R. C.N.R.S. 6599, Universit e de Technologie de Compi egne, B.P. 20529, 60205 Compi egne Cedex, France e-mail : [email protected] Abstract. An adaptive fuzzy diagnosis system is presented for diagnosis of incipient sensor faults in an environmental process. Simulations demonstrate the capabilities of the system to detect the occure...