Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model
There is a growing body of literature which recognizes the importance of mechanical equipment reliability during processing, and reliability assessment is important in guaranteeing the precision, function, and use life span of mechanical equipment. For products with a long lifetime and high reliabil...
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doaj-4d5925daa4f74aa0aca06e6108f099cd2020-11-24T21:21:10ZengMDPI AGApplied Sciences2076-34172018-09-0189161910.3390/app8091619app8091619Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature ModelWei Dai0Yongjiao Chi1Zhiyuan Lu2Meiqing Wang3Yu Zhao4School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, ChinaSchool of Mechanical Engineering and Automation, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaThere is a growing body of literature which recognizes the importance of mechanical equipment reliability during processing, and reliability assessment is important in guaranteeing the precision, function, and use life span of mechanical equipment. For products with a long lifetime and high reliability, it is difficult to assess lifetime and reliability using traditional statistical inference based on a large sample of data from the lifetime test. Therefore, this study contributed to this growing area of research, through a reliability evaluation method based on degradation path distribution related to signal characteristics. In this research, an effective method for reliability assessment was constructed, in which the signal features of the machining process were used to replace traditional time data and fit equipment degradation model. The pseudo failure characteristic (PFC) was obtained according to the failure threshold and the reliability curve was plotted by a PFC distribution model. Experimental investigation on tool reliability assessment was used to verify the effectiveness of this method, in which the trend that tool wear changes with the features was fitted by a Gaussian distribution function and Logarithmic distribution function, to obtain a better tool degradation model. The results illustrated the model could evaluate reliability of mechanical equipment effectively.http://www.mdpi.com/2076-3417/8/9/1619performance degradationdegradation pathreliability assessment |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wei Dai Yongjiao Chi Zhiyuan Lu Meiqing Wang Yu Zhao |
spellingShingle |
Wei Dai Yongjiao Chi Zhiyuan Lu Meiqing Wang Yu Zhao Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model Applied Sciences performance degradation degradation path reliability assessment |
author_facet |
Wei Dai Yongjiao Chi Zhiyuan Lu Meiqing Wang Yu Zhao |
author_sort |
Wei Dai |
title |
Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model |
title_short |
Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model |
title_full |
Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model |
title_fullStr |
Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model |
title_full_unstemmed |
Research on Reliability Assessment of Mechanical Equipment Based on the Performance–Feature Model |
title_sort |
research on reliability assessment of mechanical equipment based on the performance–feature model |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2018-09-01 |
description |
There is a growing body of literature which recognizes the importance of mechanical equipment reliability during processing, and reliability assessment is important in guaranteeing the precision, function, and use life span of mechanical equipment. For products with a long lifetime and high reliability, it is difficult to assess lifetime and reliability using traditional statistical inference based on a large sample of data from the lifetime test. Therefore, this study contributed to this growing area of research, through a reliability evaluation method based on degradation path distribution related to signal characteristics. In this research, an effective method for reliability assessment was constructed, in which the signal features of the machining process were used to replace traditional time data and fit equipment degradation model. The pseudo failure characteristic (PFC) was obtained according to the failure threshold and the reliability curve was plotted by a PFC distribution model. Experimental investigation on tool reliability assessment was used to verify the effectiveness of this method, in which the trend that tool wear changes with the features was fitted by a Gaussian distribution function and Logarithmic distribution function, to obtain a better tool degradation model. The results illustrated the model could evaluate reliability of mechanical equipment effectively. |
topic |
performance degradation degradation path reliability assessment |
url |
http://www.mdpi.com/2076-3417/8/9/1619 |
work_keys_str_mv |
AT weidai researchonreliabilityassessmentofmechanicalequipmentbasedontheperformancefeaturemodel AT yongjiaochi researchonreliabilityassessmentofmechanicalequipmentbasedontheperformancefeaturemodel AT zhiyuanlu researchonreliabilityassessmentofmechanicalequipmentbasedontheperformancefeaturemodel AT meiqingwang researchonreliabilityassessmentofmechanicalequipmentbasedontheperformancefeaturemodel AT yuzhao researchonreliabilityassessmentofmechanicalequipmentbasedontheperformancefeaturemodel |
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1726000597293858816 |