{"title":"A Comparison of Machine Health Indicators Based on the Impulsiveness of Vibration Signals","authors":"Bingchang Hou, Dong Wang, Tongtong Yan, Zhike Peng","doi":"10.1007/s40857-021-00224-7","DOIUrl":null,"url":null,"abstract":"<div><p>Vibration signals collected from machines can contain rich machine degradation information, such as impulsiveness and cyclo-stationarity. In the field of machine condition monitoring (MCM), quantification of impulsiveness has attracted many researchers’ interests because impulsiveness often indicates an occurrence of incipient faults. Impulsiveness-based health indicators (HIs) (e.g., Gini index, kurtosis, entropy, smoothness index, etc.) are some kinds of statistical parameters that can quantify the impulsiveness of vibration signals. Hence, they have been widely studied during recent years for MCM. However, a thorough comparitive study of those HIs is seldom reported. This paper aims to compare seven impulsiveness-based HIs including kurtosis, skewness, smoothness index, negative entropy, Gini index, Hoyer measure, and the ratio of L2 to L1 norm for MCM according to three properties including the robustness to the length of a signal, the gradient for sparsity or impulsiveness, and quantification of impulsiveness and cyclo-stationarity. Among the seven HIs, it was experimentally found that the Gini index is better than the other indicators to satisfy the three suggested properties for MCM.</p></div>","PeriodicalId":54355,"journal":{"name":"Acoustics Australia","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2021-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40857-021-00224-7","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acoustics Australia","FirstCategoryId":"101","ListUrlMain":"https://link.springer.com/article/10.1007/s40857-021-00224-7","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Vibration signals collected from machines can contain rich machine degradation information, such as impulsiveness and cyclo-stationarity. In the field of machine condition monitoring (MCM), quantification of impulsiveness has attracted many researchers’ interests because impulsiveness often indicates an occurrence of incipient faults. Impulsiveness-based health indicators (HIs) (e.g., Gini index, kurtosis, entropy, smoothness index, etc.) are some kinds of statistical parameters that can quantify the impulsiveness of vibration signals. Hence, they have been widely studied during recent years for MCM. However, a thorough comparitive study of those HIs is seldom reported. This paper aims to compare seven impulsiveness-based HIs including kurtosis, skewness, smoothness index, negative entropy, Gini index, Hoyer measure, and the ratio of L2 to L1 norm for MCM according to three properties including the robustness to the length of a signal, the gradient for sparsity or impulsiveness, and quantification of impulsiveness and cyclo-stationarity. Among the seven HIs, it was experimentally found that the Gini index is better than the other indicators to satisfy the three suggested properties for MCM.
期刊介绍:
Acoustics Australia, the journal of the Australian Acoustical Society, has been publishing high quality research and technical papers in all areas of acoustics since commencement in 1972. The target audience for the journal includes both researchers and practitioners. It aims to publish papers and technical notes that are relevant to current acoustics and of interest to members of the Society. These include but are not limited to: Architectural and Building Acoustics, Environmental Noise, Underwater Acoustics, Engineering Noise and Vibration Control, Occupational Noise Management, Hearing, Musical Acoustics.