Search results for "Fault Detection"
showing 10 items of 77 documents
Vibration analysis for bearing fault detection and classification using an intelligent filter
2014
Abstract This paper proposes an intelligent method based on artificial neural networks (ANNs) to detect bearing defects of induction motors. In this method, the vibration signal passes through removing non-bearing fault component (RNFC) filter, designed by neural networks, in order to remove its non-bearing fault components, and then enters the second neural network that uses pattern recognition techniques for fault classification. Four different categories include; healthy, inner race defect, outer race defect, and double holes in outer race are investigated. Compared to the regular fault detection methods that use frequency-domain features, the proposed method is based on analyzing time-d…
Fault diagnosis and modeling of the liquids packaging process. A research based on Petri Nets
2008
Searching for solutions to manufacture industries, which every day deal with problems of faults in their process, that generate economics and humans main losses, an algorithm to construct a Petri Nets based model and diagnoser to isolate and fault detection of discrete events systems is presented. This algorithm is developed in a real process of liquids packaging, where we can see that its implementation allows detecting individuals, simultaneous and dependents faults. The process to construct the model and diagnoser is systematic and useful, and it reduces the problems of combinational explosion, which is the main problem present in other investigations. This research has an excellent proj…
Investigation of motor current signature and vibration analysis for diagnosing rotor broken bars in double cage induction motors
2012
This paper investigates the detectability of rotor broken bars in double cage induction motors using current signature and vibration analysis techniques. Double cage induction motors are commonly used for applications where successive loaded starts-up are mandatory. Experimental results were performed under healthy and faulty cases, and for different load conditions using each technique. Rotor broken bars fault detection based on sideband current components may fails due to the presence of inter bar currents that reduce the degree of rotor asymmetry, yielding to a decrease of the magnitude of these spectral components. But inter bar currents produce core vibrations in the axial direction, w…
Robust Control Allocation for Spacecraft Attitude Stabilization under Actuator Faults and Uncertainty
2014
A robust control allocation scheme is developed for rigid spacecraft attitude stabilization in the presence of actuator partial loss fault, actuator failure, and actuator misalignment. First, a neural network fault detection scheme is proposed, Second, an adaptive attitude tracking strategy is employed which can realize fault tolerance control under the actuator partial loss and actuator failure withinλmin=0.5. The attitude tracking and faults detection are always here during the procedure. Once the fault occurred which could not guaranteed the attitude stable for 30 s, the robust control allocation strategy is generated automatically. The robust control allocation compensates the control …
A robust calibration methodology for an On-Board Diagnostic car system
2006
New car models are now by law equipped with on-board diagnostic (OBD) systems aimed at monitoring the state of health of strategic components that ensure low levels of polluting exhaust emissions. During development phases, for each new car model, the OBD system must be finely calibrated. This article presents a robust calibration methodology taking into account sources of variability mainly due to production process, operating, and environmental conditions. The methodology enables us to evaluate the false alarm and failure to detect risks intrinsically related to the adopted calibration. An application concerning an upstream oxygen sensor monitored by the OBD is presented.
A two-stage fault detection and classification for electric pitch drives in offshore wind farms using support vector machine
2017
This article presents a two-stage fault detection and classification scheme, for induction motor drives in wind turbine pitch systems. The presented approach is suitable for application in offshore wind farms. The adopted strategy utilizes three phase motor current sensing at the pitch drives for fault detection and only when a fault is detected at this stage, features extracted from the current signals are transmitted to a central support vector machine classifier. The proposed method is validated in a laboratory setup of the pitch drive.
Data-driven design of robust fault detection system for wind turbines
2014
Abstract In this paper, a robust data-driven fault detection approach is proposed with application to a wind turbine benchmark. The main challenges of the wind turbine fault detection lie in its nonlinearity, unknown disturbances as well as significant measurement noise. To overcome these difficulties, a data-driven fault detection scheme is proposed with robust residual generators directly constructed from available process data. A performance index and an optimization criterion are proposed to achieve the robustness of the residual signals related to the disturbances. For the residual evaluation, a proper evaluation approach as well as a suitable decision logic is given to make a correct …
Arc Fault Detection Method Based on CZT Low-Frequency Harmonic Current Analysis
2017
This paper presents a method for the detection of series arc faults in electrical circuits, which has been developed starting from an experimental characterization of the arc fault phenomenon and an arcing current study in several test conditions. Starting from this, the authors have found that is it possible to suitably detect arc faults by means of a high-resolution low-frequency harmonic analysis of current signal, based on chirp zeta transform, and a proper set of indicators. The proposed method effectiveness is shown by means of experimental tests, which were carried in both arcing and nonarcing conditions and in the presence of different loads, chosen according to the UL 1699 standard…
A robust fault detection design for uncertain Takagi-Sugeno models with unknown inputs and time-varying delays
2013
Abstract This paper investigates the problem of robust fault detection system design for a class of uncertain Takagi–Sugeno (T–S) models. The system under consideration is subject to unknown input and time-varying delay. The fault detection system is designed such that the unknown input is thoroughly decoupled from residual signals generated by the fault detection system. Furthermore, the residual signals show the maximum possible sensitivity to the faults and the minimum possible sensitivity to the external disturbances. The model matching approach is utilized to tackle the effects of parametric uncertainties in the model of the system. The design procedure is presented in terms of Linear …
A structured filter for Markovian switching systems
2014
In this work, a new methodology for the structuring of multiple model estimation schemas is developed. The proposed filter is applied to the estimation and detection of active mode in dynamic systems. The discrete-time Markovian switching systems represented by several linear models, associated with a particular operating mode, are studied. Therefore, the main idea of this work is the subdivision of the models set to some subsets in order to improve the detection and estimation performances. Each subset is associated with sub-estimators based on models of the subset. In order to compute the global estimate and subset probabilities, a global estimator is proposed. Theoretical developments ba…