K. Koshekov, Yu. N. Klikushin, V. Kobenko, Y. Evdokimov, A. Demyanenko
{"title":"Fuel Cell Diagnostics Using Identification Measurement Theory","authors":"K. Koshekov, Yu. N. Klikushin, V. Kobenko, Y. Evdokimov, A. Demyanenko","doi":"10.1115/1.4027395","DOIUrl":null,"url":null,"abstract":"The possibility to use instruments of identification measurement theory to solve the problems of diagnostics of fuel cells according to their noise characteristics is considered in this paper. The offered techniques of diagnostic signals processing are based on the identification measurement of time and probabilistic characteristics, the comparison of model signals with the ones under analysis according to the reading values, the classification of signals according to the waveform parameter and characteristic frequency, the building of hierarchical structures, and the assessment of the signal structures by the fractal indices. All proposed techniques are applicable for the diagnosis of a fuel cell, but thanks to graphical representation of classification trees of noise signals, the more efficient method for experts is the one based on the building of hierarchical structures.","PeriodicalId":15829,"journal":{"name":"Journal of Fuel Cell Science and Technology","volume":"11 1","pages":"051003"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1115/1.4027395","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Fuel Cell Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4027395","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
The possibility to use instruments of identification measurement theory to solve the problems of diagnostics of fuel cells according to their noise characteristics is considered in this paper. The offered techniques of diagnostic signals processing are based on the identification measurement of time and probabilistic characteristics, the comparison of model signals with the ones under analysis according to the reading values, the classification of signals according to the waveform parameter and characteristic frequency, the building of hierarchical structures, and the assessment of the signal structures by the fractal indices. All proposed techniques are applicable for the diagnosis of a fuel cell, but thanks to graphical representation of classification trees of noise signals, the more efficient method for experts is the one based on the building of hierarchical structures.
期刊介绍:
The Journal of Fuel Cell Science and Technology publishes peer-reviewed archival scholarly articles, Research Papers, Technical Briefs, and feature articles on all aspects of the science, engineering, and manufacturing of fuel cells of all types. Specific areas of importance include, but are not limited to: development of constituent materials, joining, bonding, connecting, interface/interphase regions, and seals, cell design, processing and manufacturing, multi-scale modeling, combined and coupled behavior, aging, durability and damage tolerance, reliability, availability, stack design, processing and manufacturing, system design and manufacturing, power electronics, optimization and control, fuel cell applications, and fuels and infrastructure.