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Vibration analysis of rotating machines for an optimal preventive maintenance

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Face to the development and competition to competitiveness, which drives the search for quality and above ail; cost reduction, maintenance has become one of the strategic functions in the company. One of the solutions incorporated in management systems is Conditional maintenance that has proved successful; Reduce downtime, optimize manufacturing, ensure safety and profitability of production. For this type of maintenance to be effective, precise and reliable measurements are required. Experience has shown that vibration analysis is the most widely used technique for reliable monitoring and diagnosis. The objective of this work is the study carried out at the Elma Labiod cement plant, which has adopted continuous monitoring in the hope of an optimal approach to conditional maintenance. We use the analysis of global velocity and acceleration levels, spectral analysis and envelope analysis to detect defects and anticipate degradations that can affect a mechanism and determine the probable causes of these malfunctions. In this context, the actual measurements were analyzed by vibratory indicator leading to detection of the weak points causing a malfunction on the machine (rolling bearings), therefor an optimization of the maintenance is realized by monitoring the degradation through on-line control system. The analysis of these vibrations let the possibility to detect and locale the defective components once the fixed corresponding threshold limit of vibration level has been reached.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
191--202
Opis fizyczny
Bibliogr. 17 poz., rys.
Twórcy
autor
  • Department of Mining Engineering, University of Tebessa, Tebessa,Algeria
autor
  • Laboratory of Transport Engineering and Environment, Mentouri University-Constantine, Algeria.
Bibliografia
  • BELHOUR S., 2008. Contribution to optimizing predictive maintenance By using the software OMNITREND (on line system) Case: Cement Hamma bouziane. doctoral thesis in mechanical sciences, University of Constantine, Algeria, 90.
  • BERTRAND R., 2000. Detection and localization of failures on an electrical drive doctoral thesis in electrical energy. National Polytechnic Institute of Grenoble - INPG.
  • BOULENGER A., 2006, predictive maintenance by vibration analysis, Engineering Technique. MT 9 285,77-84.
  • BOULENGER.A, PACHAUD C, 2003. Maintenance vibration analysis: monitoring and diagnostics of industrial management series machines, Dunod, Paris.
  • BRENEUR C., 2002. Elements of preventive maintenance of rotating machines in the case of combined defects of gears and bearings, doctoral thesis, doctoral school of sciences for the engineer of lyon.
  • CHAIB R., 2009. Contribution to the optimization of predictive maintenance by vibratory analysis, doctoral thesis in mechanical sciences, University of Constantine, Algeria.
  • DJEBILI O., 2013. Contribution to the predictive maintenance by vibration analysis of rotating mechanical components. Application to ball bearings subject to rolling contact fatigue, University of Reims Champagne-Ardenne.
  • DUCHEMIN G., 2006. Engineering technology BM 4 188, Maintenance of machinery and engines.
  • EUGENE D., EFAGA, 2004. Analysis of feedback data for the organization of maintenance of SME / SMI equipment in the framework of the MBF (reliability-based maintenance), doctoral thesis, ULPUY I N° :LEPSI-EA 3118.
  • IUNG B., LEVRAT E.,THOMAS E., 2007. Odds Algorithm’-based Opportunistic Maintenance Task Execution for Preserving Product Conditions, Annals of the CIRP vol. 56/1.
  • KNIGHT R., 2001. "State of the art monitoring and diagnosis of rotating equipment to EDF" RFM.
  • MARIE-LINE ZANI 2003. Mechanical measurements monitoring of rotating machinery buying guide, 77-84.
  • ORHAN S., NIZAMI A., VELI C., 2006. Vibration Monitoring for Defect Diagnosis of Rolling element bearings as a predictive maintenance tool: Comprehensive case studies, NDT&E International 39, 293–298.
  • OULMANE A., 2014. Monitoring and fault diagnosis of rotating machinery in the field using time frequency neural networks and fuzzy logic, doctoral thesis in Mechanical Engineering University of Montreal.
  • VASSELIN J.L., COMBET F., 2015. Contribution of collecting raw time signals for vibration monitoring of a single production site, feedback, 22nd French Congress of Mechanics.
  • ZANI M. L., 2003. Mechanical measurements monitoring of rotating machinery buying guide, pp 77-84.
  • http://www.westchinacement.com/ Group structure & MANAGEMENT TEAM consulté le 14 /03/2017.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-06ee2f29-880e-42b3-a73a-8e0cf2d20651
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