Title :
A method of operational reliability assessment for equipment based on dynamic degradation signal
Author_Institution :
Sch. of Mech. & Electron. Eng., Xi´´an Technol. Univ., Xi´´an, China
Abstract :
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.
Keywords :
condition monitoring; feature extraction; preventive maintenance; production equipment; reliability; rolling bearings; statistical analysis; vibrations; dynamic degradation signal; dynamic monitoring data; equipment condition monitoring; equipment dynamic vibration signal feature extraction; equipment operational reliability assessment; preventive maintenance; proportional hazards model; rolling bearing; statistical analysis; Condition monitoring; Couplings; Degradation; Feature extraction; Hazards; Life estimation; Lifetime estimation; Probability; Statistics; Vibration measurement; monitoring information; proportional hazards models; reliability; vibration signal;
Conference_Titel :
Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4903-3
Electronic_ISBN :
978-1-4244-4905-7
DOI :
10.1109/ICRMS.2009.5270159