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Gears are used for the transfer of mechanical power and are an important part of the electromechanical transmission system. Unexpected failure of gear could cause shutdown of the machines and proves to be expensive in terms of production loss and maintenance. Therefore, reliable condition monitoring is required to protect unexpected gear failures. It has been highlighted in the recently published...
A generic framework for estimating the reliability of equipment is through “information fusion” of its failure history, predictive maintenance data and domain expert's knowledge is proposed and demonstrated. The framework uses “Degree of Certainty” arrived at using fuzzy sets and “Belief” & “Plausibility” measures to arrive at a decision on the effectiveness of predictive maintenance. Uncertainty,...
Equipment Health Monitoring through Predictive Maintenance (PDM) data is proposed and the same is demonstrated with case study. Steel Rolling Mill Gearbox is considered for the purpose. Empirical failure rate model using Equipment Health Index (EHI) is proposed and used it for forecasting maintenance requirements of the process equipment. The strength of the proposed approach lies in integrating multiple...
Process plants like integrated steel plants use thousands of electric motors as prime movers of process equipment. The reliability of motors, especially large motors in the range of several hundreds of kilowatt capacity is vital as breakdown of these motors leads to breakdown of major facilities which these drive and cause large production losses. The maintenance of these large motors is often planned...
In this paper, a brief description of evanescent wave fiber optic methane sensor for the detection of methane gas in the range of 0-10% has been given. The Fiber Bragg grating (FBG) based strain sensor for condition monitoring of steel rope has been described. Laboratory model of both the sensors and their results have been enunciated. Fiber optic, being a dielectric, non-metallic, non-sparking, free...
This paper assesses the effectiveness and reliability of monitoring techniques for real-time fault detection in bearings of induction motor. The bearing failure modes and the characteristic bearing frequencies associated with the physical construction of the bearings are examined. Experimental results of vibration spectra with different faults are included, for a 7.5 kW cage induction motor, to demonstrate...
This paper proposes a novel approach for bearing health evaluation using Lempel-Ziv complexity and time domain statistical parameters in conjunction with ANFIS. Compared to conventional techniques the presented approach works well for a non linear physical system and is thus suited for condition monitoring of machine system under varying operating and loading conditions. The performance of this technique...
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