A distributed networked approach for fault detection of large-scale systems

Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available. This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units. The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem. Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique

Open-phase fault operation on multiphase induction 3 motor drives

Hugo Guzman, Ignacio Gonzalez, Federico Barrero and Mario Durán (2015). Open-Phase Fault Operation on Multiphase Induction Motor Drives, Induction Motors - Applications, Control and Fault Diagnostics, Dr. Raul Gregor (Ed.), ISBN: 978-953-51-2207-4, InTech, DOI: 10.5772/60810. Available from: http://www.intechopen.com/books/induction-motors-applications-control-and-fault-diagnostics/open-phase-fault-operation-on-multiphase-induction-motor-drivesMultiphase machines have been recognized in the last few years like an attractive alternative to conventional three-phase ones. This is due to their usefulness in a niche of applications where the reduction in the total power per phase and, mainly, the high overall system reliability and the ability of using the multiphase machine in faulty conditions are required. Electric vehicle and railway traction, all-electric ships, more-electric aircraft or wind power generation systems are examples of up-to-date real applications using multiphase machines, most of them taking advantage of the ability of continuing the operation in faulty conditions. Between the available multiphase machines, symmetrical five-phase induction machines are probably one of the most frequently considered multiphase machines in recent research. However, other multiphase machines have also been used in the last few years due to the development of more powerful microprocessors. This chapter analyzes the behavior of generic n-phase machines (beingn any odd number higher than 3) in faulty operation (considering the most common faulty operation, i.e. the open phase fault). The obtained results will be then particularized to the 5-phase case, where some simulation and experimental results will be presented to show the behavior of the entire system in healthy and faulty conditions. The chapter will be organized as follows: First, the different faults in a multiphase machine are analyzed. Fault conditions are de tailed and explained, and the interest of a multiphase machine in the management of faults is stated. The effect of the open-phase fault operation in the machine model is then studied. A generic n-phase machine is considered, being n any odd number greater than three. The analysis is afterwards particularized to the 5-phase machine, where the open phase fault condition is managed using different control methods and the obtained results are compared. Finally, the conclusions are presented in the last section of the chapter

Increasing communication reliability in manufacturing environments

This paper is concerned with low cost mechanisms that can increase reliability of machine to machine and machine to cloud communications in increasingly complex manufacturing environments that are prone to disconnections and faults. We propose a novel distributed and cooperative sensing framework that supports localized real time predictive analytics of connectivity patterns and detection of a range of faults together with issuing of notifications and responding on demand queries. We show that our Fault and Disconnection Aware Smart Sensing (FDASS) framework achieves significantly lower packet loss rates and communication delays in the face of unreliable nodes and networks when compared to the state of the art and benchmark approaches