New Particle Filter Based on GA for Equipment Remaining Useful Life Prediction

Li, Ké; Wu, Jingjing; Zhang, Qiuju; Su, Lei; Chen, Peng

doi:10.3390/s17040696

Cited by 24 publications

(16 citation statements)

References 25 publications

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“…Since there is a number of punches that is equal to the number of windows that exist in the bearing cage, at a single work stroke of the central conical mandrel, all of the windows are cut. incorporated in such systems, and principles corresponding to the mechanical systems could be taken into consideration when analyzing the roller bearing and its manufacture [11][12][13][14][15].…”

Section: Theoretical Analysismentioning

confidence: 99%

“…Within these patents, only the processes and equipment for obtaining windows in bearing cages were discussed, without offering details about the dimensional precision of the cages' windows that were obtainable by such manufacturing processes. Even the roller bearings are not complex systems; they could be incorporated in such systems, and principles corresponding to the mechanical systems could be taken into consideration when analyzing the roller bearing and its manufacture [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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The Dimensional Precision of Forming Windows in Bearing Cages

et al. 2018

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In the case of double row tapered roller bearings, the windows found in bearing cages could be obtained using various machining methods. Some such machining methods are based on the cold forming process. There are many factors that are able to affect the machining accuracy of the windows that exist in bearing cages. On the dimensional precision of windows, the clearance between punches and die, the work stroke length, and the workpiece thickness could exert influence. To evaluate this influence, experimental research was developed taking into consideration the height and the length of the cage window and the distance between the contact elements of the cage. By mathematical processing of the experimental results, empirical mathematical models were determined and analyzed. The empirical models highlighted the intensity of the influence exerted by the considered forming process input factors on the dimensional precision of the windows obtained in bearing cages.

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Section: Theoretical Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Dimensional Precision of Forming Windows in Bearing Cages

et al. 2018

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“…In this paper, the particle filter method is employed because it can deal with nonlinear models with non-Gaussian noise. In the past, the particle filter method had been used for remaining useful life prediction and prognosis of bearings, lithium ion batteries, fatigue crack growth, gas turbine, LED lumen, compressor, planetary-carrier gear plate [11,[20][21][22][23][24][25][26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Prognosis of gas turbine remaining useful life using particle filter approach

Ahsan

Lemma

Muhammad

2019

Materialwissenschaft Werkst

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Gas turbines are commonly used in distributed power generation. Because of high speed nature, they require good maintenance for increased reliability and availability. Remaining useful life prediction is therefore an essential part of condition‐based maintenance to better foresee future state hence guaranteeing design efficiency, reduced maintenance cost, and improved safety. Gas turbines also contain a lot of sensors data that need to be processed for better prediction. In this paper, a probabilistic approach called particle filter is used for prediction. The proposed approach is tested using Turbofan degradation data provided by NASA as a benchmark problem. Meanwhile, through time the gas turbines experiences a change from normal state to degraded state attributed to aging, corrosion and erosion etc. Hence, in the context of abundant data, it is helpful to know the transition between states. For the same reason, the present paper suggests a statistical approach called Z‐test. The test results show that the proposed technique provides score and MAPE values of 559.9 and 21.6 respectively, comparable to past reported performance.

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“…In particular, the Kalman filter and extended Kalman filter, which can provide the analytical solutions of the linear Gaussian Bayesian filter, were extensively applied to track fatigue and corrosion propagation of structural elements [ 6 , 7 , 8 , 9 ]. On the other hand, the particle filter approach, which is a simulation based empirical solution of the Bayesian filter, gained subsequent but remarkable spotlight in recent years [ 10 , 11 , 12 , 13 ]. This is mainly due to its wide applicability to various model structures and also drastic improvement of computational capabilities, which now enables real-time estimations [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Particle Filter Based Monitoring and Prediction of Spatiotemporal Corrosion Using Successive Measurements of Structural Responses

Song

2018

Sensors

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Prediction of structural deterioration is a challenging task due to various uncertainties and temporal changes in the environmental conditions, measurement noises as well as errors of mathematical models used for predicting the deterioration progress. Monitoring of deterioration progress is also challenging even with successive measurements, especially when only indirect measurements such as structural responses are available. Recent developments of Bayesian filters and Bayesian inversion methods make it possible to address these challenges through probabilistic assimilation of successive measurement data and deterioration progress models. To this end, this paper proposes a new framework to monitor and predict the spatiotemporal progress of structural deterioration using successive, indirect and noisy measurements. The framework adopts particle filter for the purpose of real-time monitoring and prediction of corrosion states and probabilistic inference of uncertain and/or time-varying parameters in the corrosion progress model. In order to infer deterioration states from sparse indirect inspection data, for example structural responses at sensor locations, a Bayesian inversion method is integrated with the particle filter. The dimension of a continuous domain is reduced by the use of basis functions of truncated Karhunen-Loève expansion. The proposed framework is demonstrated and successfully tested by numerical experiments of reinforcement bar and steel plates subject to corrosion.

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New Particle Filter Based on GA for Equipment Remaining Useful Life Prediction

Cited by 24 publications

References 25 publications

The Dimensional Precision of Forming Windows in Bearing Cages

The Dimensional Precision of Forming Windows in Bearing Cages

Prognosis of gas turbine remaining useful life using particle filter approach

Particle Filter Based Monitoring and Prediction of Spatiotemporal Corrosion Using Successive Measurements of Structural Responses

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