Practical machinery vibration analysis and predictive maintenance

Machinery Vibration Analysis and Predictive Maintenance provides a detailed examination of the detection, location and diagnosis of faults in rotating and reciprocating machinery using vibration analysis. The basics and underlying physics of vibration signals are first examined. The acquisition and...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Girdhar, Paresh
Συγγραφή απο Οργανισμό/Αρχή: ScienceDirect (Online service)
Άλλοι συγγραφείς: Scheffer, C ((Cornelius))
Μορφή: Ηλεκτρονική πηγή Βιβλίο
Γλώσσα:English
Έκδοση: Amsterdam Boston Burlington, MA Elsevier Newnes 2004
Σειρά:Practical professional books from Elsevier
Θέματα:
Διαθέσιμο Online:An electronic book accessible through the World Wide Web; click for information
An electronic book accessible through the World Wide Web; click for information
Publisher description
Table of contents
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020 |a 9780750662758 
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041 0 |a eng 
050 4 |a TJ177  |b .G49 2004eb 
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100 1 |a Girdhar, Paresh  |9 74533 
245 1 0 |a Practical machinery vibration analysis and predictive maintenance  |h [electronic resource]  |c Paresh Girdhar; edited by C. Scheffer 
260 |a Amsterdam  |a Boston  |a Burlington, MA  |b Elsevier  |b Newnes  |c 2004 
300 |a vi, 255 σ.  |b εικ.  |c 27 εκ 
490 0 |a Practical professional books from Elsevier 
500 |a Περιέχει ευρετήριο 
505 1 |a Machinery Vibration Analysis and Predictive Maintenance provides a detailed examination of the detection, location and diagnosis of faults in rotating and reciprocating machinery using vibration analysis. The basics and underlying physics of vibration signals are first examined. The acquisition and processing of signals is then reviewed followed by a discussion of machinery fault diagnosis using vibration analysis. Hereafter the important issue of rectifying faults that have been identified using vibration analysis is covered. The book also covers the other techniques of predictive maintenance such as oil and particle analysis, ultrasound and infrared thermography. The latest approaches and equipment used together with the latest techniques in vibration analysis emerging from current research are also highlighted 
520 |a Machinery Vibration Analysis and Predictive Maintenance provides a detailed examination of the detection, location and diagnosis of faults in rotating and reciprocating machinery using vibration analysis. The basics and underlying physics of vibration signals are first examined. The acquisition and processing of signals is then reviewed followed by a discussion of machinery fault diagnosis using vibration analysis. Hereafter the important issue of rectifying faults that have been identified using vibration analysis is covered. The book also covers the other techniques of predictive maintenance such as oil and particle analysis, ultrasound and infrared thermography. The latest approaches and equipment used together with the latest techniques in vibration analysis emerging from current research are also highlighted. 1.Understand the basics of vibration measurement 2.Apply vibration analysis for different machinery faults 3.Diagnose machinery-related problems with vibration analysis techniques 
650 4 |a Μηχανήματα  |9 64882 
650 4 |a Δόνηση  |9 37509 
650 4 |a Μηχανήματα  |x Συντήρηση και επισκευή  |9 74084 
700 1 |a Scheffer, C  |q ((Cornelius))  |9 74538 
710 2 |a ScienceDirect (Online service)  |9 35187 
760 1 |a Practical professional books from Elsevier 
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856 4 0 |3 ScienceDirect  |u http://www.sciencedirect.com/science/book/9780750662758  |z An electronic book accessible through the World Wide Web; click for information 
856 4 0 |3 Referex  |u http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780750662758  |z An electronic book accessible through the World Wide Web; click for information 
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856 4 1 |3 Table of contents  |u http://www.loc.gov/catdir/enhancements/fy0627/2005299230-t.html 
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952 |0 0  |1 0  |4 0  |6 621_811000000000000_GIR  |7 0  |9 76005  |a LISP  |b LISP  |d 2016-04-24  |l 0  |o 621.811 GIR  |r 2016-04-24  |w 2016-04-24  |y ERS