Software reliability for business applications is becoming a topic of interest in the IT community. An effective method to validate and understand defect behaviour in a software application is Fault Injection. Fault i...Software reliability for business applications is becoming a topic of interest in the IT community. An effective method to validate and understand defect behaviour in a software application is Fault Injection. Fault injection involves the deliberate insertion of faults or errors into software in order to determine its response and to study its behaviour. Fault Injection Modeling has demonstrated to be an effective method for study and analysis of defect response, validating fault-tolerant systems, and understanding systems behaviour in the presence of injected faults. The objectives of this study are to measure and analyze defect leakage;Amplification Index (AI) of errors and examine “Domino” effect of defects leaked into subsequent Software Development Life Cycle phases in a business application. The approach endeavour to demonstrate the phasewise impact of leaked defects, through causal analysis and quantitative analysis of defects leakage and amplification index patterns in system built using technology variants (C#, VB 6.0, Java).展开更多
Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong bac...Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.展开更多
文摘Software reliability for business applications is becoming a topic of interest in the IT community. An effective method to validate and understand defect behaviour in a software application is Fault Injection. Fault injection involves the deliberate insertion of faults or errors into software in order to determine its response and to study its behaviour. Fault Injection Modeling has demonstrated to be an effective method for study and analysis of defect response, validating fault-tolerant systems, and understanding systems behaviour in the presence of injected faults. The objectives of this study are to measure and analyze defect leakage;Amplification Index (AI) of errors and examine “Domino” effect of defects leaked into subsequent Software Development Life Cycle phases in a business application. The approach endeavour to demonstrate the phasewise impact of leaked defects, through causal analysis and quantitative analysis of defects leakage and amplification index patterns in system built using technology variants (C#, VB 6.0, Java).
基金co-supported by the Fundamental Research Funds for the Central Universities of China,China Postdoctoral Science Foundation(No.2018M631196)the National Natural Foundation of China(No.51705420).
文摘Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.
