Classification of acoustic emission signals generated from journal bearing at different lubrication conditions based on wavelet analysis in combination with artificial neural network and genetic algorithm

Author:

Sadegh Hosseini,Mehdi Ahmadi Najafabadi,Mehdi Akhlaghi

Publisher

Elsevier BV

Subject

Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanical Engineering,Mechanics of Materials

Reference30 articles.

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2. An efficient approach to machine health diagnosis based on harmonic wavelet packet transform;Ruqiang;Robot Comput-Integr Manuf,2005

3. ASTM E 569-597. Standard practice for acoustic emission monitoring of structures during controlled stimulation.

4. Development of acoustic emission technology for the condition monitoring and diagnosis of rotating machines: bearings, pumps, gearboxes, engines and rotating structures;Mba;Shock Vib Dig,2006

5. Baranov V, Kudryavtsev E, Sarychev G, Schavelin V. Simulation of characteristics of acoustic emission in friction. In: Acoustic emission in friction. Tribology and interface engineering series, no. 53; 2007. p. 67–71 (Acoustic emission in friction. Available from ERDC Library, ISBN: 9780080451503, 1st ed. Elsevier, Amsterdam, Boston, 2007; xii, 218 pp.)

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