The classification of acoustic emission source mechanisms based on features related to the physics of acoustic emission
signal generation is considered in this paper. Numerically generated acoustic emission waveforms are used for this
purpose. Conventional acoustic emission parameters such as rise-time, duration, and frequency content do not
effectively characterize acoustic emission waveforms for the purpose of identifying the source mechanisms. Features
unique to the different source mechanisms and relative positions of the sensor with respect to the source were identified
and extracted from numerically obtained acoustic emission waveforms. This feature selection appears to be successful in
capturing the differences related to the source mechanisms considered here. Correlation coefficients of the 45 features
with different waveforms were first obtained, and their principal components determined. The dominant principle
components were found to adequately characterize the waveforms and relate them to their source mechanisms. Better
than 90 percent success was seen when only the first two principle components were employed, even in noisy signals
considered here.
Identification of the source mechanism and measurement of source strength are important requirements for wider field
application of the acoustic emission technique. It is difficult to relate a given source event to resulting acoustic emission
waveforms in experimental results. However, it is practical to simulate such source events using numerical simulations
and examine the resulting waveforms. The present paper uses such an approach to identify the patterns embedded in the
waveforms and their variation with relative positions of the source and sensor. Important elements in the waveforms are
shown to have strong variation with respect to the relative positions of the source and sensor. The resulting amplitude
variations should be taken into account in the measurement of acoustic emission source strength. In addition, it is shown
that the shear horizontal wave has a prominent component in the normal stresses in the radial direction. Acoustic
emission waveforms obtained from the numerical simulations were also used to demonstrate pattern classification of
these waveforms and identify the source mechanisms. The three elements of the waveforms, So, Ao, and Shear, were
considered as the basic elements of the waveform. These elements have different frequency bandwidths that are directly related to the impulse duration of the incremental crack growth. Correlation coefficients between these elements and the acoustic emission waveforms were used as a means for identifying the source type.
We present an initial ontology for tactical behaviors conducted by unmanned ground vehicles (UGVs). We focus on
activities, which are the denotations of verbs, notably 'move' but also 'look (for)' and several others. These take
collective subjects, allowing activities to be attributed to units at various hierarchical levels. The semantics of verbs
must consider the denotations of their grammatical complements; that is, we must consider entire verb frames. The
thematic relations of the noun-phrase complements are critical, but prepositions also play an important role. FrameNet is
an online lexical database of frames derived from text corpora. Our other major resource is Levin's classification of
verbs according to how changes in their frames affect their meanings. Although natural languages have a large variety
of words for aspects of tactical behaviors, there is motivation to get by with as few basic verbs as possible. A variety of
meanings can often be associated with a verb by altering its frame, and we can impose co-reference constraints on
combinations of frames to generate structures denoting more complex activities. A simple grammar is developed for the
verbs of interest. Protege-Frames ontologies include classes that inherit from linguistically inspired classes but capture
domain-specific notions.
We address spatial ontologies for the areas of operations of tactical behaviors carried out by unmanned ground vehicles
(UGVs). An ontology is a conceptualization of a domain and provides a common vocabulary for automated applications
in the domain of interest. Ontological concepts are typically qualitative yet are rigorously defined. An ontology should
provide abstract concepts that allow meaningful generalizations. The work reported here is the first known attempt to
apply spatial ontologies to tactical behaviors. Some research on spatial ontologies is based on point set topology,
although many find points to be unnatural primitives. Alternatives include relations defined in terms of the primitive
binary relation "connected_to" on regions; the "part_of" relation is also important. This paper includes a focused survey
driven by examples in which we evaluate the strengths and weaknesses of the different approaches for the domain in
question. We also develop new concepts and techniques especially applicable to representing and reasoning about areas
of operation in which UGVs perform missions.
A multiagent framework for data acquisition, analysis, and diagnosis in health management is proposed. It uses the contract net protocol, a protocol for high-level distributed problem solving that provides adaptive and flexible solutions where task decomposition and assignment of subtasks is natural. Java is used to wrap implementations of existing techniques for individual tasks, such as neural networks or fuzzy rule bases for fault classification. The Java wrapping supplies an agent interface that allows an implementation to participate in the contract net protocol. This framework is demonstrated with a simple Java prototype that monitors a laboratory specimen that generates acoustic emission signals due to fracture-induced failure. A multiagent system that conforms to our framework can focus resources as well as select important data and extract important information. Such a system is extensible and decentralized, and redundancy in it provides fault tolerance and graceful degradation. Finally, the flexibility inherent in such a system allows new strategies to develop on the fly. The behavior of a non-trivial concurrent system (such as multiagent systems) is too complex and uncontrollable to be thoroughly tested, so methods have been developed to check the design of a concurrent system against formal specifications of the system’s behavior. We review one such method-model checking with SPIN-and discuss how it can be used to verify control aspects of multiagent systems that conform to our framework.
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