Reciprocating machinery condition monitoring - Elghamry, Mohamed
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This book describes several techniques using Acoustic Emission (AE) to monitor the performance of the reciprocating machinery. It illustrate the data acquisition system setup, including sensors, signal conditioning and computer hardware and software. Several computational data analysis techniques are used to interpret the raw AE data into meaningful information. The experiments focus on the automatic evaluation of running conditions including fuel mixture strength, speed and in-cylinder pressure, but the detection of a number of common machinery faults is also demonstrated. A range of…mehr

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Produktbeschreibung
This book describes several techniques using Acoustic Emission (AE) to monitor the performance of the reciprocating machinery. It illustrate the data acquisition system setup, including sensors, signal conditioning and computer hardware and software. Several computational data analysis techniques are used to interpret the raw AE data into meaningful information. The experiments focus on the automatic evaluation of running conditions including fuel mixture strength, speed and in-cylinder pressure, but the detection of a number of common machinery faults is also demonstrated. A range of machines, from a small diesel engine to a large marine engine and a process hyper-compressor have been investigated in order to develop an approach that is generic to all reciprocating machines. The results of these investigations are discussed in the light of published work on acceleration monitoring of reciprocating machines and the author's own acceleration measurements. Conclusions are drawn on the potential of acoustic emission to provide an on-line diagnostics for a range of reciprocating machines.
Autorenporträt
Dr Mohamed Elghamry works as the Dean of the Technical & Vocational Institute at the Arab Academy for Science, Technology & Maritime Transport in Alexandria, Egypt. With a strong mechatronics experience background, he developed many projects towards product localization and renewable energy utilization, fault findings and diagnosis.