Vibration Monitoring of Rolling Element Bearings by the High-frequency Resonance Technique PDF Download

Author: P. D. McFadden
Publisher:
ISBN:
Category : Bearings (Machinery)
Languages : en
Pages : 102

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Author: P. D. McFadden
Publisher:
ISBN:
Category : Machinery
Languages : en
Pages : 78

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Book Description

Author: Mohsen M. Alwa
Publisher:
ISBN:
Category :
Languages : en
Pages : 83

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Book Description

Author: Hamid Faghidi
Publisher:
ISBN:
Category : University of Ottawa theses
Languages : en
Pages :

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Book Description
Rolling element bearings are one of the most significant elements and frequently-used components in mechanical systems. Bearing fault detection and diagnosis is important for preventing productivity loss and averting catastrophic failures of mechanical systems. In industrial applications, bearing life is often difficult to predict due to different application conditions, load and speed variations, as well as maintenance practices. Therefore, reliable fault detection is necessary to ensure productive and safe operations. Vibration analysis is the most widely used method for detection and diagnosis of bearing malfunctions. A measured vibration signal from a sensor is often contaminated by noise and vibration interference components. Over the years, many methods have been developed to reveal fault signatures, and remove noise and vibration interference components. Though many vibration based methods have been proposed in the literature, the high frequency resonance (HFR) technique is one of a very few methods have received certain industrial acceptance. However, the effectiveness of the HFR methods depends, to a great extent, on some parameters such as bandwidth and centre frequency of the fault excited resonance, and window length. Proper selection these parameters is often a knowledge-demanding and time-consuming process. In particular, the filter designed based on the improperly selected bandwidth and center frequency of the fault excited resonance can filter out the true fault information and mislead the detection/diagnosis decisions. In addition, even if these parameters can be selected properly at beginning of each process, they may become invalid in a time-varying environment after a certain period of time. Hence, they may have to be re-calculated and updated, which is again a time-consuming and error-prone process. This undermines the practical significance of the above methods for online monitoring of bearing conditions. To overcome the shortcomings of existing methods, the following four non-parametric and non-filtering methods are proposed: 1. An amplitude demodulation differentiation (ADD) method, 2. A calculus enhanced energy operator (CEEO) method, 3. A higher order analytic energy operator (HO_AEO) approach, and 4. A higher order energy operator fusion (HOEO_F) technique. The proposed methods have been evaluated using both simulated and experimental data.

Author: Atul Andhare
Publisher: LAP Lambert Academic Publishing
ISBN: 9783838357942
Category :
Languages : en
Pages : 128

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Book Description
Rolling bearings are the most important machine elements. Proper functioning of a machine depends on condition of bearings. Vibrations help in diagnosing various faults in machines. Therefore, vibration based condition monitoring is the most popular method to know health of any machine. However, as found from the literature, vibration monitoring and diagnostics of faults in tapered roller bearing is not well established. This book is therefore focused on vibration based condition monitoring of tapered roller bearings. It presents results of experiments performed towards diagnosis of defects in tapered roller bearings using vibration analysis. The bearing vibration data are analyzed using various time and frequency domain techniques. The results for defect-free and defective bearings are compared to get information for defect diagnosis. A MATLAB based computer interface, which was developed for vibration signal processing and diagnostics, is also discussed in the book. This interface made use of all the time and frequency domain vibration data to diagnose defects in bearings. This book will be useful for the practicing engineers and students working on condition monitoring.

Author: IMechE (Institution of Mechanical Engineers)
Publisher: John Wiley & Sons
ISBN: 9781860584473
Category : Technology & Engineering
Languages : en
Pages : 750

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Book Description
This essential text contains the papers from the 8th international IMechE conference on Vibrations in Rotating Machinery held at the University of Wales, Swansea in September 2004. The themes of the volume are new developments and industrial applications of current technology relevant to the vibration and noise of rotating machines and assemblies. TOPICS INCLUDE Rotor balancing – including active and automatic balancing Special rotating machines – including micromachines Oil film bearings and dampers Active control methods for rotating machines Smart machine technology Dynamics of assembled rotors Component life predictions and life extension strategies The dynamics of geared systems Cracked rotors – detection, location ad prognosis Chaotic behaviour in machines Experimental methods and discoveries.

Author: I. M. Howard
Publisher:
ISBN: 9780731696888
Category : Airplanes
Languages : en
Pages : 16

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Book Description
Vibration analysis using the high frequency resonance technique has been used successfully to detect incipient failure in rolling element bearings. This memo outlines a new method of obtaining the demodulated narrow band envelope of a bearing vibration signal from the high frequency resonant response. Previous techniques have used an analogue envelope where the raw analogue signal is bandpass filtered and enveloped before digitising. The method outlined in this document first digitises the vibration signal, performs a complex demodulation operation, then computes the envelope followed by its spectrum. Fault repetition frequencies can be identified in the demodulated spectrum of the high frequency resonant response. Keywords: Vibration tests; Demodulation; Bearing stress; Resonant frequency; Australia. (jhd).

Author: P. D. McFadden
Publisher:
ISBN: 9780642116772
Category : Signal processing
Languages : en
Pages : 18

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It is shown that the existing comb filter model of time domain averaging does not correctly describe the extraction of periodic waveforms from additive noise using a digital computer because it assumes a knowledge of the signal over an infinite time and the result it produces is not exactly periodic. A revised model is presented which requires only a finite number of samples and which produces a result which is periodic. It is demonstrated that the rejection of periodic noise of a known frequency can be optimized by the selection of a suitable number of averages.

Author:
Publisher:
ISBN:
Category : Shock (Mechanics)
Languages : en
Pages : 594

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Book Description

Author: William T. Thomson
Publisher: Cambridge University Press
ISBN: 1108489974
Category : Business & Economics
Languages : en
Pages : 309

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Book Description
Master the art of vibration monitoring of induction motors with this unique guide to on-line condition assessment and fault diagnosis, building on the author's fifty years of investigative expertise. It includes: *Robust techniques for diagnosing of a wide range of common faults, including shaft misalignment and/or soft foot, rolling element bearing faults, sleeve bearing faults, magnetic and vibrational issues, resonance in vertical motor drives, and vibration and acoustic noise from inverters. *Detailed technical coverage of thirty real-world industrial case studies, from initial vibration spectrum analysis through to fault diagnosis and final strip-down. *An introduction to real-world vibration spectrum analysis for fault diagnosis, and practical guidelines to reduce bearing failure through effective grease management. This definitive book is essential reading for industrial end-users, engineers, and technicians working in motor design, manufacturing, and condition monitoring. It will also be of interest to researchers and graduate students working on condition monitoring.