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The traditional approaches to reliability estimation are based on probability statistics depending on large sample failure lifetime data. Such approaches yield statistical results that reflect average characteristics of the same kind of systems, under the same condition. They can not gain a particular individuals reliability ability. Dynamic monitoring data based on condition can provide with useful information about the reliability assessment for the equipment. By using reliability modeling techniques with equipment condition feature and information measures, a new methodology of reliability assessment based on equipment dynamic vibration signal feature extraction using proportional hazards model is proposed. The proposed approach can establish a linkage between equipment condition monitoring information and reliability statistics. It is suitable for providing effective individuals reliability assessment by equipment vibration-based degradation signal. The reliably operational ability of equipment is enhanced. This can afford equipment technical support for the preventive maintenance of reliability-centered based on equipment condition. Finally, a practice example of key component, namely rolling bearing is given to demonstrate that the method is valid and reasonable.