Search results for " Fault detection"
showing 10 items of 13 documents
Robust fault detection for switched systems with time-varying delay using delta operator approach
2014
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.
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…
Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life
2018
Bearings are one of the most critical components in electric motors, gearboxes and wind turbines. Therefore, bearing fault detection and prognosis of remaining useful life are important to prevent productivity losses. In this study, a novel method is proposed for prognosis of bearing life using an autoencoder and recurrent neural networks-based prediction algorithm. Promising results have been obtained from the experimental data. A monotonic upward trend of the produced health indicator is obtained for all test cases, being one of critical indicators of a proper prognosis. The remaining useful life estimation is moderately accurate under a limited data.
Characterization of DC series arc faults in PV systems based on current low frequency spectral analysis
2021
Abstract This work presents an experimental study focused on the characterization of series arc faults in direct current (DC) photovoltaic (PV) systems. The aim of the study is to identify some relevant characteristics of arcing current, which can be obtained by means of low frequency spectral analysis of current signal. On field tests have been carried out on a real PV system, in accordance with some tests requirements of UL 1699B Standard for protection devices against PV DC arc faults. Arcing and non-arcing current signals are acquired and compared and the behavior of a set of indicators proposed by authors is analyzed. Different measurement equipment have been used, in order to study th…
Mixed l-/l1 fault detection observer design for positive switched systems with time-varying delay via delta operator approach
2014
Published version of an article in the journal: International Journal of Control, Automation and Systems. Also available from the publisher at: http://dx.doi.org/10.1007/s12555-013-0466-1 This paper investigates the problem of fault detection observer design for positive switched systems with time-varying delay via delta operator approach. A new fault sensitivity measure, called l-index, is proposed. The l- fault detection observer design and multi-objective l -/l1 fault detection observer design problems are addressed. Based on the average dwell time approach and the piecewise copositive type Lyapunov-Krasovskii functional method in delta domain, sufficient conditions for the existence of …
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…
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 …
A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault
2020
This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.
Modeling and Verification of Symbolic Distributed Applications Through an Intelligent Monitoring Agent
2022
Wireless Sensor Networks (WSNs) represent a key component in emerging distributed computing paradigms such as IoT, Ambient Intelligence, and Smart Cities. In these contexts, the difficulty of testing, verifying, and monitoring applications in their intended scenarios ranges from challenging to impractical. Current simulators can only be used to investigate correctness at source code level and with limited accuracy. This paper proposes a system and a methodology to model and verify symbolic distributed applications running on WSNs. The approach allows to complement the distributed application code at a high level of abstraction in order to test and reprogram it, directly, on deployed network…