Patent ID: 11893547
Assignee: CHINA UNIVERSITY OF MINING AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 2:
3. The intelligent reliability evaluation and service life prediction method for the kilometer deep well hoist brake according to claim 1, wherein the method further comprises:
Step I, acquiring, for a preset duration range in a direction from a current time to a historical time, a fourth data for the target hoist brake corresponding to the braking working condition parameters over time in the preset duration range and specifying a fifth data for second braking performance parameters related to performance degradation, and then entering Step II;
Step II, constructing, for each of the second braking performance parameters related to the performance degradation respectively, according to the fifth data for the second braking performance parameters of the target hoist brake related to the performance degradation over the time obtained in Step I, a degradation process model function as a performance degradation model corresponding to the second braking performance parameters related to the performance degradation;
further acquiring a plurality of performance degradation models corresponding to the second braking performance parameters related to the performance degradation respectively, and then entering Step III;
and Step III, acquiring, according to the plurality of performance degradation models corresponding to the second braking performance parameters related to the performance degradation respectively, for the fourth data for the braking working condition parameters obtained by detecting the target hoist brake, service life prediction results corresponding to the second braking performance parameters related to the performance degradation respectively;
wherein the Steps I to III are performed according to a second preset period duration based on the digital twin model to implement the service life prediction on the target hoist brake.