The Case-Based Module for Identifying the Signals Used in Acoustic-Emission Monitoring of Complex Technical Objects
DOI:
https://doi.org/10.24160/1993-6982-2020-4-122-128Keywords:
case-based approach, monitoring, data analysis, acoustic emissionAbstract
The article addresses the topical issues of achieving more efficient operation of the module for identifying the signals obtained during acoustic-emission monitoring of complex technical objects that involves case-based reasoning. Monitoring systems process large amounts of information that require significant time resources for manually processing them by a human (an expert or operator). Therefore, for rendering help to experts (operators), it is proposed to use machine learning methods and data mining tools. Unfortunately, in these tasks it is not always possible to obtain the necessary data set (a training sample) for effectively using the machine learning tools.
In view of the above, it is proposed to apply the advanced approach known as case-based reasoning which is actively used in artificial intelligence systems, and which is able to operate with small volumes of the training sample and accumulate experience in solving such problems. However, this approach has a significant drawback: with an increase in the number of precedents, so does the number of comparison operations for processing a new situation (task). This can be solved by using the case similarity matrix. Instead of periodically reducing the base of accumulated cases, which is a time-consuming procedure, it is proposed to limit the number of accumulated use-cases and maintain the most significant (characteristic) ones.
In addition, a case presentation of the signal spectrum is proposed to reduce the time spent on one operation of comparing two use-cases. Not only does the proposed method of representing the signal spectrum reduce the amount of processed information, but it also simplifies the metric for comparing use-cases.
These modifications can significantly increase the efficiency (throughput) of the case-based module for identifying acoustic emission signals developed in the MS Visual Studio environment in the C# language. The results of testing the module on real acoustic emission monitoring data have confirmed the validity of applying the proposed modifications for the developed case-based module.
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Для цитирования: Варшавский П.Р., Барат В.А., Кожевников А.В. Прецедентный модуль для идентификации сигналов при акустикоэмиссионном мониторинге сложных технических объектов // Вестник МЭИ. 2020. № 4. С. 122—128. DOI: 10.24160/1993-6982-2020-4-122-128.
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Работа выполнена при поддержке: РФФИ (гранты № 18-01-00459, № 18-29-03088)
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For citation: Varshavskiy P.R., Barat V.A., Kozhevnikov A.V. The Case-Based Module for Identifying the Signals Used in Acoustic- Emission Monitoring of Complex Technical Objects. Bulletin of MPEI. 2020;4:122—128. (in Russian). DOI: 10.24160/1993-6982-2020-4-122-128.
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The work is executed at support: RFBR (Grantst No. 18-01-00459, No. 18-29-03088)
