A Comparative Study of Unknown-Input Observers for Prognosis Applied to an Electromechanical System

Gucik‐Derigny, David; Outbib, Rachid; Ouladsine, Mustapha

doi:10.1109/tr.2015.2494682

Cited by 12 publications

(8 citation statements)

References 29 publications

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“…It is worth noting that this strategy was originally used for continuous deterministic model based on observers' design (see [14]). Despite the relevance of the results obtained in prognostic, uncertainty was not taken into consideration.…”

Section: Problem Statement and Prognosis Methodologymentioning

confidence: 99%

“…In this case, the techniques used to estimate degradation are based either on observers or on the Interacting Multiple Model. For example, the conventional observer approach that can be envisaged for studying determinist systems prognosis is highlighted in [14]. The second type is dedicated to the stochastic models (see, e.g., [15,16]) and Bayesian filters [17,18].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The PV Corrosion Fault Prognosis Based on Ensemble Kalman Filter

Ouladsine

Outbib

Bakhouya

2017

International Journal of Photoenergy

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The degradation of photovoltaic (PV) modules remains a major concern on the control and the development of the photovoltaic field, particularly, in regions with difficult climatic conditions. The main degradation modes of the PV modules are corrosion, discoloration, glass breaks, and cracks of cells. However, corrosion and discoloration remain the predominant degradation modes that still require further investigations. In this paper, a model-based PV corrosion prognostic approach, based on an ensemble Kalman filter (EnKF), is introduced to identify the PV corrosion parameters and then estimate the remaining useful life (RUL). Simulations have been conducted using measured data set, and results are reported to show the efficiency of the proposed approach.

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Section: Problem Statement and Prognosis Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The PV Corrosion Fault Prognosis Based on Ensemble Kalman Filter

Ouladsine

Outbib

Bakhouya

2017

International Journal of Photoenergy

Self Cite

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“…Note that observers can be used to monitor and track the states and parameters affected by degradation. 70,74,75 In this example, the unmeasured K a parameter (damage evolution) can be estimated (tracking) and the quality of the estimate will depend on the observer used. For our work, we assume that the parameter is not observable.…”

Section: Case Studiesmentioning

confidence: 99%

Remaining useful life estimation based on the joint use of an observer and a hidden Markov model

Aggab

Vrignat

Avila

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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We propose an approach for failure prognosis based on the estimation of the Remaining Useful Life (RUL) of a system in a situation in which monitoring signals providing information about its degradation evolution are not measured and no operating model of the system is available. These conditions are of practical interest for industrial applications such as mechanical (e.g. rolling bearing) or electrical (e.g. wind turbine) devices or equipment-critical components (e.g. batteries) in which the addition of sensors to the system is not feasible (e.g. space limitations for sensors, cost, etc.). The approach is based on an estimation of the system degradation using residual generation (where the difference between the system and the observer outputs is processed) and Hidden Markov Models with discrete observations. The prediction of the system RUL is given by the Markov property concerning the mean time before absorption. The approach comprises two phases: a training phase to model the degradation behavior and an “on-line” use phase to estimate the remaining life of the system. Two case studies were conducted for RUL prediction to verify the effectiveness of the proposed approach.

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“…Ten sets of input-output data using the same command input signal 1 V are obtained from the actual electric scooter system. Each set is used for parameter identification based on GA with the fitness function in (19). For each parameter, the mean calculated from the ten sets of identified parameters is treated as the nominal value, and the maximum deviation from the mean value divided by the mean value is considered as the multiplicative uncertainty value [7].…”

Section: Parameter Identification and Model Validationmentioning

confidence: 99%

“…Compared with the diagnosis, the prognosis is more efficient in achieving fault prevention, thus prolonging the system lifetime [13]. Due to this property, many works have been done recently in prognosis for a variety of systems [14][15][16][17][18][19][20]. In [14], an artificial intelligence (AI) based method utilizing the fuzzy identification technique is developed.…”

Section: Introductionmentioning

confidence: 99%

Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties

Wang

et al. 2020

Actuators

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This paper addresses diagnosis and prognosis problems for an electric scooter subjected to parameter uncertainties and compound faults (i.e., permanent fault and intermittent fault with non-monotonic degradation). First, the diagnostic bond graph in linear fractional transformation form is used to model the uncertain electric scooter and derive the analytical redundancy relations incorporating the nominal part and uncertain part, based on which the adaptive thresholds for robust fault detection and the fault signature matrix for fault isolation can be obtained. Second, an adaptive enhanced unscented Kalman filter is proposed to identify the fault magnitudes and distinguish the fault types where an auxiliary detector is introduced to capture the appearing and disappearing moments of intermittent fault. Third, a dynamic model with usage dependent degradation coefficient is developed to describe the degradation process of intermittent fault under various usage conditions. Due to the variation of degradation coefficient and the presence of non-monotonic degradation characteristic under some usage conditions, a sequential prognosis method is proposed where the reactivation of the prognoser is governed by the reactivation events. Finally, the proposed methods are validated by experiment results.

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A Comparative Study of Unknown-Input Observers for Prognosis Applied to an Electromechanical System

Cited by 12 publications

References 29 publications

The PV Corrosion Fault Prognosis Based on Ensemble Kalman Filter

The PV Corrosion Fault Prognosis Based on Ensemble Kalman Filter

Remaining useful life estimation based on the joint use of an observer and a hidden Markov model

Compound Fault Diagnosis and Sequential Prognosis for Electric Scooter with Uncertainties

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