This paper introduces the theory of cyclic statistics as a powerful tool for the diagnosis of gear faults. More precisely, a new method based on the cyclic bispectrum, a third order cyclic statistical function, is use...
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This paper introduces the theory of cyclic statistics as a powerful tool for the diagnosis of gear faults. More precisely, a new method based on the cyclic bispectrum, a third order cyclic statistical function, is used for monitoring. This estimator furnishes a valuable means of detecting and characterising non-linear coupling effects as well as any periodic correlation between different components in machines. Therefore, the cyclic bispectrum provides much more combined information than classical methods such as spectrum and cepstrum analysis. Application to the diagnosis of spalling of the gear teeth of the U.S. Navy helicopter demonstrates the effectiveness of this new parameter for a good diagnosis.
Providing an accurate position estimate is a challenging problem that has to be faced in different fields. Several solutions have been proposed to harness this challenging issue. In this paper, we analyze the dynamic ...
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Providing an accurate position estimate is a challenging problem that has to be faced in different fields. Several solutions have been proposed to harness this challenging issue. In this paper, we analyze the dynamic performance of a MEMS accelerometer tailored to precision pointing devices applications. The prototype consists of a testing board equipped with a single MEMS accelerometer and a microprocessor mounted within a PC-mouse. An embedded application takes care of position estimation and data transmission. Two main problems will be addressed, namely the influence of the attitude angle and of irregularities in the working surface on the position reconstruction from measured data. The overall analysis process is performed on experimental data. To assess the position reconstruction performance we employed a motion capture system for measuring the true device position.
In this paper, a bolus tracking algorithm was proposed for the Computed Tomography Angiography (CTA) under a realistic constraint, bolus density is monitored through a narrow temporal window. The objective of the cont...
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In this paper, a bolus tracking algorithm was proposed for the Computed Tomography Angiography (CTA) under a realistic constraint, bolus density is monitored through a narrow temporal window. The objective of the control is to predict the bolus peak position so the synchronization of temporal window and bolus peak position can be obtained.
A control strategy is developed in order to maximize the production of lipase for a process operating in fed batch mode. At first, an original method based on the mathematical properties of the model is proposed to de...
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A control strategy is developed in order to maximize the production of lipase for a process operating in fed batch mode. At first, an original method based on the mathematical properties of the model is proposed to define a closed loop control strategy. The strategy elaborated consists in regulating the substrate/biomass ratio at a given set point, which requires the design of a specific controller able to cope with the process non linearities. A linearizing controller is proposed. Then, to implement it on the process, an adaptive version of the controller is developped by coupling it with an estimation algorithm. The control system is tested and proved performant even under realistic conditions with noise on the output and disturbances on the kinetic parameters.
This paper presents a new estimation algorithm, which is essentially a modification of the weighted recursive least squares algorithm (W-RLS), for systems with bounded disturbances. Assuming the knowledge of a disturb...
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This paper presents a new estimation algorithm, which is essentially a modification of the weighted recursive least squares algorithm (W-RLS), for systems with bounded disturbances. Assuming the knowledge of a disturbance upper bound, the algorithm's derivation is performed the minimization of a cost function weighted by two factors : one is fixed by the user and exponentially weights the arrival information, the other is time-varying and data-dependent. The purpose of the latter is to ensure the algorithm stability faced with the bounded disturbances and to enhance the convergence rate, as much as permitted by the available data. The final algorithm has a very compact and simple form. It completely depends upon the significative information and it stops when the arrival data are redundant. After the algorithm derivation, the paper presents the convergence properties, analyses the algorithm behavior faced with time-varying systems and presents some simulations.
Cells in a clonal cell-population exhibit a significant degree of heterogeneity in their responses to an external stimulus. In order to model a heterogeneous intracellular process, the individual-based population mode...
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Cells in a clonal cell-population exhibit a significant degree of heterogeneity in their responses to an external stimulus. In order to model a heterogeneous intracellular process, the individual-based population model (IBPM) has been developed in the past. Specifically, the IBPM approach can represent the heterogeneous dynamics in a cell population with a system of differential equations, whose model parameters follow probability density functions (PDF) instead of being constants. Therefore, in order to accurately predict the heterogeneous cellular dynamics, it is important to infer the PDFs of the model parameters from available experimental measurements. In this study, we propose a methodology to estimate the PDFs of the model parameters from population snapshot measurements obtained from flow cytometry. First, the PDFs of the model parameters are assumed to be normal so that a finite dimensional vector will be inferred from the measurements instead of inferring PDFs. Second, the sensitivity analysis is performed to identify which PDFs of the model parameters are identifiable and should be estimated from the available measurements. Next, in order to reduce the excessive number of evaluations of the IBPM during the PDF estimation process, an NNM is developed so that the output PDFs can be computed for given parameter PDFs. Lastly, the NNM is used to estimate the PDFs of the model parameters by minimizing the difference between the measured and predicted PDFs of the output. To show the effectiveness of the proposed methodology, the PDFs of parameters of a TNFα signaling model were estimated from in silico measurements.
This paper studies the problem of multi-agent cooperative localization of a common reference coordinate frame in ℝ 3 . Each agent in a system maintains a body-fixed coordinate frame and its actual frame transformation...
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This paper studies the problem of multi-agent cooperative localization of a common reference coordinate frame in ℝ 3 . Each agent in a system maintains a body-fixed coordinate frame and its actual frame transformation (translation and rotation) from the global coordinate system is unknown. The mobile agents aim to determine their trajectories of rigid-body motions (or the frame transformations, i.e., rotations and translations) with respect to the global coordinate frame up to a common frame transformation by using local measurements and information exchanged with neighbors. We present two frame localization schemes which compute the rigid-body motions of the agents with asymptotic stability and finite-time stability properties, respectively. Under both localization laws, the estimates of the frame transformations of the agents converge to the actual frame transformations almost globally and up to an unknown constant transformation bias. Finally, simulation results are provided.
An adaptive Kalman filter was designed to shape the covariance of a quadrature encoder signal to achieve better performance under measurement quantisation. Both temporal and system state measurements were used to pred...
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An adaptive Kalman filter was designed to shape the covariance of a quadrature encoder signal to achieve better performance under measurement quantisation. Both temporal and system state measurements were used to predict the measurement noise of the encoder. Results show that the new adaptive filter produces more accurate results while requiring a lower resolution encoder than a similarly designed conventional Kalman filter intended to remove quantisation noise. An example with simulated output is presented to show the performance of the new filter.
This paper accurately quantifies the way in which noise induced estimation errors are dependent on model structure, underlying system frequency response, measurement noise and input excitation. This exposes several ne...
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This paper accurately quantifies the way in which noise induced estimation errors are dependent on model structure, underlying system frequency response, measurement noise and input excitation. This exposes several new principles. In particular, it is shown here that when employing Output–Error model structures in a prediction-error framework, then the ensuing estimate variability in the frequency domain depends on the underlying system pole positions. As well, it is also established that the variability is affected by the choice of model structure, in that it is twice as much when system poles are estimated as when they are a-priori known and fixed, even though the model order is the same in both cases. These results are unexpected according to pre-existing theory.
Many patients undergo long-term artificial ventilation and their respiratory system mechanics should be monitored to detect changes in the patient's state and to optimize ventilator settings. In this work the most...
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Many patients undergo long-term artificial ventilation and their respiratory system mechanics should be monitored to detect changes in the patient's state and to optimize ventilator settings. In this work the most popular algorithms for tracking the variations of respiratory resistance and elastance over a ventilatory cycle were analysed in terms of systematic and random errors. Additionally, a new algorithm was proposed and compared to the previous ones. The results of analyses showed the advantages of this new approach and enabled to form several suggestions concerning the respiratory mechanics monitoring during artificial ventilation.
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