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Between August and September, 2021, this study included 605 SARS-CoV-2 natural infection cases and 589 SARS-CoV-2 breakthrough cases from Nanjing and Yangzhou, as well as 690 inactivated COVID-19 vaccine recipients from Changzhou, China. In SARS-CoV-2 natural infection cases, the age range was 19-91 years (median age: 66 year), and the medians(选取2021年8—9月南京和扬州市新型冠状病毒肺炎（新冠肺炎）疫情中的新冠肺炎病例和免疫突破病例，以及常州市新型冠状病毒灭活疫苗免疫人群为研究对象，分别纳入605例新冠病毒自然感染病例、589名免疫突破病例和690例新冠灭活疫苗免疫者。新冠病毒自然感染病例年龄为19~91岁，年龄

The purpose of this paper is to study the reliability life calculation model of aerial rolling bearing considered the correlation of failure model. By mean of collecting relevant experiment data of vibration signal and temperature signal in the life test of the aerial rolling bearings, and analyse time domain and frequency domain, we can analyse the main failure modes and mechanism (e.g. wear, fatigue). The characteristic parameters that characterize the healthy state of aerial rolling bearings obviously are extracted further. Considering that the bearings expose multiple failure modes in the working process in most case, bearing fault diagnosis method is based on fuzzy theory. It is used to clarify the failure mechanism of different failure modes and the degradation rule of performance characteristic parameters. It’s very essential that establish the clear relationships between performance degradation and symptomatic set. According to the fault diagnosis results, each of failure modes is established the performance degradation model respectively. Considering the correlation between multiple different failure modes, Copula theory is introduced to analyse the correlation between multiple failure modes. Base on Copula theory, it’s obtained the life distribution model of aerial bearing based on multiple failure modes. Life distribution model are verified by subsequent experiments, which show that life distribution model of aerial rolling bearing in this paper, is feasible and necessary.