Acoustic emission mapping of diesel engines for spatially located time series—Part II: Spatial reconstitution
TL;DR: In this article, the authors investigated the characteristics of AE wave transmission around and through the cylinder head of a small four-stroke fuel injection diesel engine, using a nine-sensor array.
About: This article is published in Mechanical Systems and Signal Processing.The article was published on 2007-02-01. It has received 41 citations till now. The article focuses on the topics: Cylinder head & Acoustic emission.
Citations
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TL;DR: In this article, the air-borne acoustic signals in the vicinity of injector head were recorded using three microphones around the fuel injector (120° apart from each other) and an independent component analysis (ICA) based scheme was developed to decompose these acoustic signals.
121 citations
Additional excerpts
...J.D. Gill, R.L. Reuben, J.A. Steel (2000), A study of small HSDI diesel engine fuel injection equipment faults using acoustic emission, in: Proceedings of the EWGAE, 24th European Conference on Acoustic Emission Testing, Paris, France, 281–286....
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...P. Nivesrangsan, J.A. Steel, R.L. Reuben (2007)....
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TL;DR: In this paper, two source location techniques, a traditional wave velocity-based and an energy-based technique, using triangular sensor arrays, are used to locate source positions on the cylinder head of a 74kW diesel engine using simulated sources (pencil lead break) and real sources (e.g. injectors and exhaust valves during engine running).
74 citations
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TL;DR: In this paper, the authors presented a theoretical investigation of the acoustic emission to detect the internal leakage rate through a valve and experimental validation of the AE signals generated by internal liquid and gas leakage through valves.
68 citations
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01 Feb 2008
TL;DR: In this paper, acoustic emission testing for faults in static equipment has been used since the 1970s, but its use as a monitoring technology for various machinery conditions has been poorly adopted by industry, despite a significant volume of work having been published over the past twenty years describing success in detecting rotating and reciprocating machinery faults.
Abstract: Managing asset integrity is crucial for the cost-effective asset management of processing plants. Consequently, new techniques for detection and classification of incipient faults are continuously being sought by industry and developed by research and development professionals, both corporate and academic. Although acoustic emission (AE) testing for faults in static equipment has been used since the 1970s, its use as a monitoring technology for various machinery conditions has been poorly adopted by industry, despite a significant volume of work having been published over the past twenty years describing success in detecting numerous rotating and reciprocating machinery faults. Anecdotal evidence from industry suggests that many ‘tried and failed’. The authors believe that this is because applying AE monitoring to industrial plant is fraught with poorly documented challenges, obstacles, and limitations that must be well understood and overcome before any reported results can be replicated. Thus, t...
67 citations
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20 Jun 2014
TL;DR: This paper presents a review of recent literature in the field of acoustic emission signal analysis through artificial intelligence in machine conditioning monitoring and fault diagnosis and limits the scope to artificial intelligence methods.
Abstract: Acoustic Emission technique is a successful method in machinery condition monitoring and fault diagnosis due to its high sensitivity on locating micro cracks in high frequency domain. A recently developed method is by using artificial intelligence techniques as tools for routine maintenance. This paper presents a review of recent literature in the field of acoustic emission signal analysis through artificial intelligence in machine conditioning monitoring and fault diagnosis. Many different methods have been previously developed on the basis of intelligent systems such as artificial neural network, fuzzy logic system, Genetic Algorithms, and Support Vector Machine. However, the use of Acoustic Emission signal analysis and artificial intelligence techniques for machine condition monitoring and fault diagnosis is still rare. Although many papers have been written in area of artificial intelligence methods, this paper puts emphasis on Acoustic Emission signal analysis and limits the scope to artificial intelligence methods. In the future, the applications of artificial intelligence in machine condition monitoring and fault diagnosis still need more encouragement and attention due to the gap in the literature.
43 citations
Cites background from "Acoustic emission mapping of diesel..."
...They discovered that the real cause of AE signals had mechanical impact and fluid flow excitation for valve events [9]....
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References
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01 Jan 1963TL;DR: A large and growing number of original papers on both the experimental and the theoretical aspects of stress wave propagation is appearing in the scientific literature, and two international conferences solely concerned with the subject have been held during the last five years as mentioned in this paper.
Abstract: A large and growing number of original papers on both the experimental and the theoretical aspects of stress wave propagation is appearing in the scientific literature, and two international conferences solely concerned with the subject have been held during the last five years. The purpose of this paper is to review recent experimental and theoretical advances in the propagation of deformation waves of arbitrary shape through elastic and anelastic solids, and also to attempt to outline the problems on which present efforts are being directed and to predict probable lines of future development.
2,063 citations
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91 citations
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TL;DR: In this paper, two source location techniques, a traditional wave velocity-based and an energy-based technique, using triangular sensor arrays, are used to locate source positions on the cylinder head of a 74kW diesel engine using simulated sources (pencil lead break) and real sources (e.g. injectors and exhaust valves during engine running).
74 citations
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TL;DR: The ultimate aim of the work, of which this paper is a part, is to provide a means of on-line automatic monitoring of reciprocating machines using AE without recourse to any additional sensors.
65 citations
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TL;DR: In this article, the authors presented the first step towards using multiple acoustic emission (AE) sensors to produce spatially located time series signals for a running engine, which is meant the decomposition of a multi-source signal by acquiring it with an array of sensors and using source location to reconstitute the individual time series attributable to some or all of these signals.
57 citations