It is difficult to obtain all the parameters for evaluating 220 kV circuit breakers. And the excessive maintenance of circuit breakers after installation and the insufficient maintenance afterwards caused by planned overhauls and sudden maintenance methods are also observed. To deal with the problems

the relationship between the temperature and state of a circuit breaker

and the circuit breaker’s degradation process with artificial repairs

are discussed in this paper. A reliability prediction model for 220 kV circuit breaker based on the Moffat resting hidden Markov model（HMM） degradation process is built

with temperature as the status evaluation parameter

and service time and status maintenance as the model modification parameters. The model describes the "Moffat rest" degradation of the health state of a circuit breaker during its entire life cycle. On this basis

the temperature of multiple key components obtained by fusing infrared detection images and visible light detection images is analyzed to evaluate and predict operating reliability of the circuit breaker. The experimental results show that the periodic repair of equipment suppresses the degradation of the time-varying state transition matrix. By analyzing the temperature of key components

the error of the state evaluation lagging behind the actual situation is decreased. Comparing the evaluations of available coefficient and outage rate with the actual data

the errors are reduced to 0.044% and 0.032% respectively. The results show that

the obtained reliability prediction of circuit breakers by using the proposed method is more in line with the law of equipment degradation.