Nonlinear Gaussian Belief Network Based Fault
Bearing fault diagnosis method based on Hilbert envelope spectrum and deep belief network
... When fault occurs in bearing, the frequency spectrum of vibration signal would change and it contains a considerable amount of fault information which can reflect the actual work condition and the ...
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Industrial fault detection and diagnosis using Bayesian belief network
... sensor fault detection module, and ...process fault. Having detected the fault, next step would be to diagnose the root cause of the fault and the propagation ...The fault may be ...
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Multi-layer neural network with deep belief network for gearbox fault diagnosis
... in fault diagnosis of gearbox. Other MLNN-based learning technologies are efficient and effective for gearbox faults diagnosis, however they may be fall into “apparent local minima or plateaus” in some ...
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A hydraulic fault diagnosis method based on sliding-window spectrum feature and deep belief network
... Fig. 7. Classification results with different training times 4.2.2. Cases in different sliding width and overlap rate The original vibration signals measured in the synthetical hydraulic fault experimental ...
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A fuzzy based Bayesian Belief Network approach for railway bridge condition monitoring and fault detection
... and fault detection tool of bridges, in or- der to achieve a reduction of the whole life cost of the asset by adopting a condition-based maintenance ...activities based on the health state of the ...
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A new fault diagnosis method using deep belief network and compressive sensing
... achieving fault diagnosis using CS compressed signal directly, because the main information is reserved in the ...incorporate nonlinear relationships between machinery states and compressed ...
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Automatic belief network modeling via policy inference for SDN fault localization
... methods based verification tools are developed to check the status after modeling network behaviors using a binary ...vert network rules (configuration and forwarding rules respectively) into boolean ...
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Covariance Intersection in Nonlinear Estimation Based on Pseudo Gaussian Densities
... complicated nonlinear estimation techniques, but the required calculations can be performed independently from the state estimation process, which solely relies on the pseudo Gaussian densities and the ...
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Model based fault diagnosis and prognosis of nonlinear systems
... a fault can be isolated as local or nonlocal to a particular subsystem based on the time when it is ...local fault detector and there is no need for the detection information to be transmitted at ...
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Robust Fuzzy Observer-based Fault Detection for Nonlinear Systems
... for fault diagnosis, there are two major problems: the first problem is that most studies only deal with steady-state ...line fault diagnosis in the presence of transient behaviors, the system dynamics have ...
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Thruster fault diagnosis method based on Gaussian particle filter for autonomous underwater vehicles
... the fault size of an actuator online; this filter can be applied in fault tolerant ...strong nonlinear system; the use of the Gaussian particle filter is this system can solve this kind of ...
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Application of Bayesian Belief Networks to system fault diagnostics
... software based, it is not difficult to maintain and it gives a quick response when sensors evidence is ...existing network, therefore the method may not be easily adaptable to substantial ...
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Real-time fault detection method based on belief rule base for aircraft navigation system
... is based on the least mean squared error measure and the parameter estimation is achieved by the traditional nonlinear programming with an off-line ...
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Fault diagnosis of gearbox based on the nonlinear output frequency response functions and PNN
... the fault diagnosis of nonlinear gearbox is investigated by using the frequency domain ...The Nonlinear Output Frequency Response Functions (NOFRFs) of the nonlinear gearbox are evaluated and ...
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Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation
... to Gaussian BP. Sufficient convergence conditions for Gaussian BP have been developed in Weiss and Freeman (2001a); Malioutov et ...underlying Gaussian distribution is expressed in terms of pairwise ...
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Fault tolerant control for nonlinear systems using sliding mode and adaptive neural network estimator
... for fault tolerant control usually uses an on-line estimator to estimate a fault, where the fault estimator can be implemented using different components and are adapted with different learning algo- ...
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Regularised Gaussian belief propagation
... REGULARISED GAUSSIAN BELIEF PROPAGATION 32 For the simulated precision matrix, we found that the spectral radius of L is 1 when λ = 0 (this is typical when the zero-diagonal spectral radius of S is ...
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Gaussian Process Belief Propagation
... the Gaussian model is ...data, belief propagation (BP) techiques can be employed, which essentially pass messages (local conditional distributions) between nodes and update the node marginals accordingly ...
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A Belief-based Approach to Network Formation
... to network formation under mutual consent can be based on the consent game introduced in Myerson ...to network formation under mutual ...empty network is always supported through a strict Nash ...
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