Nonlinear Trend Analysis of Mill Fan System Vibrations for Predictive Maintenance and Diagnostics

Hadjiski, Mincho; Doukovska, Lyubka; Kojnov, Stefan L.

doi:10.2478/v10177-012-0048-9

Cited by 1 publication

(2 citation statements)

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“…Mill fans (MF) are key element in ensuring the reliable functioning of energy boilers burning lowgrade lignite. The structural scheme of MF with the necessary signage is shown in Figure 4, but details are given in [7,8,9]. (1) where y is amplitude of vibration, the disturbances in the right side of the equation may be presented as a function of exciting mechanical disturbances (damaged bearings, unbalanceness due to wear, etc.)…”

Section: Characteristics Of Mill Fans As Objects Of Diagnosismentioning

confidence: 99%

“…Along with approved approaches based on models, intelligent methods using various techniques of computational intelligence increasingly enter: Neural Networks [16], Case Based Reasoning (CBR) [3,13,15,16], data and decision fusion [3,5,6]. A combination of different intelligent methods is increasingly observed [5,16,8] for using the advantages of each component in the hybrid scheme. Diagnosis of complex technological plants is a key element in the rapidly evolving field of Condition Based Monitoring and Maintenance (CBM) [1,9,10,12,14,16].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Consistent Data and Decision Fusion of Heterogeneous Information Denoising in Complex Systems Diagnosis

Hadjiski

Doukovska

2012

Proceedings of the First International Conference on Telecommunications and Remote Sensing

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In the diagnosis of complex industrial systems arise a lot of sever problems to solve due to the heterogeneous information sources, a large number of directly unmeasurable variables, which should be replaced by softsensing, big uncertainty of current information, temporal uncoherency of some measurements because of the very different requirements for the spectral window of corresponding signals in the different stages of the FDD (Fault Detection and Diagnosis) procedure. In the paper a hybrid approach of multistep procedure is considered for denoising of diagnostic information in order to achieve more realistic and more effective decision in a comparison with the conventional statistical approaches using some techniques from the Computational Intelligence like Neural Networks and Case-Based Reasoning. The main statements accepted in this investigation are: the different stages of complex diagnosis could require different information, different methods of partial diagnosis and different methods of decision making; the main method of hybridization is accepted to be consistent data and decision fusion; signal processing in particular diagnosis stages should be relevant to the main diagnostic goals in the stage.In the paper the proposed method for consistent fusion of data and decisions is implemented for online vibrodiagnosis of mechanical condition of the industrial mill fan of steam boiler in Power plant. 163Hadjiski M. and Doukovska L.

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Section: Characteristics Of Mill Fans As Objects Of Diagnosismentioning

confidence: 99%