Early detection and diagnosis of incipient faults is desirable for online condition assessment, product quality assurance and improved operational efficiency of induction motors running off power supply mains. In this paper, a model-based fault diagnosis system is developed for induction motors, using recurrent dynamic neural networks for transient response prediction and multi-resolution signa...

Rolling bearings are widely used in rotating equipment. Detection of bearing faults is of great importance to guarantee safe operation of mechanical systems. Acoustic emission (AE), as one of the bearing monitoring technologies, is sensitive to weak signals and performs well in detecting incipient faults. Therefore, AE is widely used in monitoring the operating status of rolling bearing. This p...

Abstract: We focus on the detection of incipient faults in an internal combustion engine using a minimum number of sensory information. Inducing several faults in a 4 stroke diesel engine, cylinder pressure (P) and vibration (V) data are acquired. Two sets of artificial neural nets (ANN) are trained separately, using features from the pressure and vibration data. Both sets of nets show very goo...

In this article, we propose a tractable nonlinear fault estimation filter along with explicit performance bounds for class of linear dynamical systems in the presence both additive and multiplicative faults. We consider case, where faults may occur simultaneously through an identical relationship, setting that is relevant to several application domains, including automotive driving, aviation, c...

Power transformers play an important role in ensuring efficient and reliable transmission distribution of electrical power. Their failure can lead to significant disruptions power supply safety concerns. Transformer incipient faults may occur due various reasons, including electrical, mechanical or environmental factors. They develop slowly serious damage if not diagnosed corrected time. In thi...

Power transformers being the major apparatus in a power system, thus the assessment of transformer operating condition and lifespan have obtained crucial significance in latest years. Dissolved gas analysis (DGA) is a sensitive and reliable technique for the detection of incipient fault condition within oil-immersed transformers, which provides the basis of diagnostic evaluation of equipment he...

By using a modified signed directed graph (SDG) together with the distributed artificial neural networks and a knowledge-based system, a method of incipient multi-fault diagnosis is presented for large-scale physical systems with complex pipes and instrumentations such as valves, actuators, sensors, and controllers. The proposed method is designed so as to (1) make a real-time incipient fault d...

With the rapid development of arts of sensors and IT, on-line monitoring of circuit breaker is now desirable and practical for electric power utilities. This paper describes a set of overall on-line monitoring systems that was developed to control and monitor the condition of SF6 circuit breaker with different type of sensors and microcomputer based controller. The aim of the developed system i...

-In this paper, a linear model based FDI framework of nonlinear Three-tank system is developed. The nonlinear model [16] is analytically linearized using perturbation theory. Simulations are carried out to verify the linearization and effectiveness of the proposed framework, for fault detection, isolation and estimation of abrupt, incipient in the presence of model uncertainties as well as for ...