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Machinery Noise and Diagnostics

Machinery Noise and Diagnostics
Author: Richard Harold Lyon
Publisher:
Total Pages: 299
Release: 1989
Genre: Machinery
ISBN:

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Machinery Noise and Diagnostics

Machinery Noise and Diagnostics
Author: Richard H Lyon, Corp
Publisher:
Total Pages: 418
Release: 1984
Genre: Machinery
ISBN:

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Machinery Noise and Diagnostics

Machinery Noise and Diagnostics
Author: Richard H Lyon
Publisher: Butterworth-Heinemann
Total Pages: 310
Release: 2013-10-22
Genre: Technology & Engineering
ISBN: 1483289451

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Approx.312 pages


Rotating Machinery and Signal Processing

Rotating Machinery and Signal Processing
Author: Ahmed Felkaoui
Publisher: Springer
Total Pages: 133
Release: 2018-07-19
Genre: Technology & Engineering
ISBN: 3319961810

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This book provides readers with a timely snapshot of the potential offered by and challenges posed by signal processing methods in the field of machine diagnostics and condition monitoring. It gathers contributions to the first Workshop on Signal Processing Applied to Rotating Machinery Diagnostics, held in Setif, Algeria, on April 9-10, 2017, and organized by the Applied Precision Mechanics Laboratory (LMPA) at the Institute of Precision Mechanics, University of Setif, Algeria and the Laboratory of Mechanics, Modeling and Manufacturing (LA2MP) at the National School of Engineers of Sfax. The respective chapters highlight research conducted by the two laboratories on the following main topics: noise and vibration in machines; condition monitoring in non-stationary operations; vibro-acoustic diagnosis of machinery; signal processing and pattern recognition methods; monitoring and diagnostic systems; and dynamic modeling and fault detection.


Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Advances in Condition Monitoring of Machinery in Non-Stationary Operations
Author: Alfonso Fernandez Del Rincon
Publisher: Springer
Total Pages: 423
Release: 2019-02-07
Genre: Technology & Engineering
ISBN: 3030112209

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This book is aimed at researchers, industry professionals and students interested in the broad ranges of disciplines related to condition monitoring of machinery working in non-stationary conditions. Each chapter, accepted after a rigorous peer-review process, reports on a selected, original piece of work presented and discussed at the International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO’2018, held on June 20 – 22, 2018, in Santander, Spain. The book describes both theoretical developments and a number of industrial case studies, which cover different topics, such as: noise and vibrations in machinery, conditioning monitoring in non-stationary operations, vibro-acoustic diagnosis of machinery, signal processing, application of pattern recognition and data mining, monitoring and diagnostic systems, faults detection, dynamics of structures and machinery, and mechatronic machinery diagnostics.


Condition Monitoring of Machinery in Non-Stationary Operations

Condition Monitoring of Machinery in Non-Stationary Operations
Author: Tahar Fakhfakh
Publisher: Springer Science & Business Media
Total Pages: 621
Release: 2012-03-19
Genre: Technology & Engineering
ISBN: 3642287689

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Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers are divided into five sections, namely: Condition monitoring of machines in non-stationary operations Modeling of dynamics and fault in systems Signal processing and Pattern recognition Monitoring and diagnostic systems Noise and vibration of machines The presented book gives the back ground to the main objective of the CMMNO 2012 conference that is to bring together scientific community to discuss the major advances in the field of machinery condition monitoring in non-stationary conditions.


Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Advances in Condition Monitoring of Machinery in Non-Stationary Operations
Author: Giorgio Dalpiaz
Publisher: Springer Science & Business Media
Total Pages: 678
Release: 2013-10-05
Genre: Technology & Engineering
ISBN: 3642393489

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This book presents the processing of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13), which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition. The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to point out the signal content that is related to the state of the monitored component particularly in non-stationary conditions.