ELECTRONIC DEVICE AND METHOD FOR ANALYZING RELIABILITY OF FACILITY
A method for analyzing reliability of facility implemented in an electronic device. The method includes obtaining alarm data from at least one equipment; generating a first prediction parameter and a first algorithm model based on the alarm data and a first model; generating a second prediction parameter and a second algorithm model based on the alarm data and a second model; determining that the first algorithm model is better than the second algorithm model based on a judgment model, the first prediction parameter, and the second prediction parameter; and generating an evaluation index based on the first algorithm model, so as to evaluate the reliability of the at least one equipment based on the evaluation index, when the first algorithm model is determined to be better than the second algorithm model.
1 . An electronic device for analyzing reliability of facility, comprising:
a communicator configured to
obtain alarm data from at least one equipment;
a processor coupled to the communicator; and
a memory coupled to the processor and storing instructions, the processor is configured to execute the instructions to:
generate a first prediction parameter and a first algorithm model based on the alarm data and a first model;
generate a second prediction parameter and a second algorithm model based on the alarm data and a second model;
determine that the first algorithm model is better than the second algorithm model based on a judgment model, the first prediction parameter, and the second prediction parameter; and
generate an evaluation index based on the first algorithm model, so as to evaluate the reliability of the at least one equipment based on the evaluation index, in response that the first algorithm model is determined to be better than the second algorithm model.
2 . The electronic device of claim 1 , wherein the processor is further configured to execute the instructions to:
generate a maximum likelihood function corresponding to the first model based on the first model, wherein the maximum likelihood function comprises undetermined parameters;
generate solutions of the undetermined parameters based on the alarm data and an algorithm model;
generate the first algorithm model based on the solutions of the undetermined parameters and the maximum likelihood function; and
generate the first prediction parameter based on the first algorithm model and an adaption model.
3 . The electronic device of claim 2 , wherein the processor is further configured to execute the instructions to:
set initial parameters of the algorithm model; and
generate the solutions of the undetermined parameters by adjusting the initial parameters based on the alarm data until the initial parameters meet a preset constraint condition.
4 . The electronic device of claim 1 , wherein the processor is further configured to execute the instructions to:
generate the first prediction parameter based on the first algorithm model and a preset Akaike information criterion (AIC);
generate the second prediction parameter based on the second algorithm model and the preset AIC;
determine that the first prediction parameter is less than or equal to the second prediction parameter based on the judgement model; and
determine that the first algorithm model is better than the second algorithm model, in response that the first prediction parameter is determined to be less than or equal to the second prediction parameter.
5 . The electronic device of claim 1 , wherein the processor is further configured to execute the instructions to:
extract calculation parameters of the first algorithm model, in response that the first algorithm model is determined to be better than the second algorithm model; and
generate the evaluation index by inputting the calculation parameters to a reliability model.
6 . The electronic device of claim 1 , wherein the alarm data comprises a first alarm category, a second alarm category, a first time set corresponding to the first alarm category, and a second time set corresponding to the second alarm category, the evaluation index comprises a Mean Time To Failure (MTTF),
the processor is further configured to execute the instructions to:
generate a first MTTF corresponding to the first alarm category based on the first time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model;
generate a second MTTF corresponding to the second alarm category based on the second time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model; and
generate a MTTF of the at least one equipment based on the first MTTF and the second MTTF.
7 . A method for analyzing reliability of facility implemented in an electronic device comprising:
obtaining alarm data from at least one equipment;
generating a first prediction parameter and a first algorithm model based on the alarm data and a first model;
generating a second prediction parameter and a second algorithm model based on the alarm data and a second model;
determining that the first algorithm model is better than the second algorithm model based on a judgment model, the first prediction parameter, and the second prediction parameter; and
generating an evaluation index based on the first algorithm model, so as to evaluate the reliability of the at least one equipment based on the evaluation index, in response that the first algorithm model is determined to be better than the second algorithm model.
8 . The method of claim 7 , wherein generating a first prediction parameter and a first algorithm model comprises:
generating a maximum likelihood function corresponding to the first model based on the first model, wherein the maximum likelihood function comprises undetermined parameters;
generating solutions of the undetermined parameters based on the alarm data and an algorithm model;
generating the first algorithm model based on the solutions of the undetermined parameters and the maximum likelihood function; and
generating the first prediction parameter based on the first algorithm model and an adaption model.
9 . The method of claim 8 , further comprising:
setting initial parameters of the algorithm model; and
generating the solutions of the undetermined parameters by adjusting the initial parameters based on the alarm data until the initial parameters meet a preset constraint condition.
10 . The method of claim 7 , wherein determining that the first algorithm model is better than the second algorithm model comprises:
generating the first prediction parameter based on the first algorithm model and a preset Akaike information criterion (AIC);
generating the second prediction parameter based on the second algorithm model and the preset AIC;
determining that the first prediction parameter is less than or equal to the second prediction parameter based on the judgement model; and
determining that the first algorithm model is better than the second algorithm model, in response that the first prediction parameter is determined to be less than or equal to the second prediction parameter.
11 . The method of claim 7 wherein generating an evaluation index comprises:
extracting calculation parameters of the first algorithm model, in response that the first algorithm model is determined to be better than the second algorithm model; and
generating the evaluation index by inputting the calculation parameters to a reliability model.
12 . The method of claim 7 , wherein the alarm data comprises a first alarm category, a second alarm category, a first time set corresponding to the first alarm category, and a second time set corresponding to the second alarm category, the evaluation index comprises a Mean Time To Failure (MTTF),
the method further comprising:
generating a first MTTF corresponding to the first alarm category based on the first time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model;
generating a second MTTF corresponding to the second alarm category based on the second time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model; and
generating a MTTF of the at least one equipment based on the first MTTF and the second MTTF.
13 . An electronic device for analyzing reliability of facility, comprising:
a processor coupled to the communicator; and
a memory coupled to the processor and storing instructions, the processor is configured to execute the instructions to:
obtain alarm data from at least one equipment;
generate a first prediction parameter and a first algorithm model based on the alarm data and a first model;
generate a second prediction parameter and a second algorithm model based on the alarm data and a second model;
determine that the first algorithm model is better than the second algorithm model based on a judgment model, the first prediction parameter, and the second prediction parameter; and
generate an evaluation index based on the first algorithm model, so as to evaluate the reliability of the equipment based on the evaluation index, in response that the first algorithm model is determined to be better than the second algorithm model.
14 . The electronic device of claim 13 , wherein the processor is further configured to execute the instructions to:
generate a maximum likelihood function corresponding to the first model based on the first model, wherein the maximum likelihood function comprises undetermined parameters;
generate solutions of the undetermined parameters based on the alarm data and an algorithm model;
generate the first algorithm model based on the solutions of the undetermined parameters and the maximum likelihood function; and
generate the first prediction parameter based on the first algorithm model and an adaption model.
15 . The electronic device of claim 14 , wherein the processor is further configured to execute the instructions to:
set initial parameters of the algorithm model; and
generate the solutions of the undetermined parameters by adjusting the initial parameters based on the alarm data until the initial parameters meet a preset constraint condition.
16 . The electronic device of claim 13 , wherein the processor is further configured to execute the instructions to:
generate the first prediction parameter based on the first algorithm model and a preset Akaike information criterion (AIC);
generate the second prediction parameter based on the second algorithm model and the preset AIC;
determine that the first prediction parameter is less than or equal to the second prediction parameter based on the judgement model; and
determine that the first algorithm model is better than the second algorithm model, in response that the first prediction parameter is determined to be less than or equal to the second prediction parameter.
17 . The electronic device of claim 13 , wherein the processor is further configured to execute the instructions to:
extract calculation parameters of the first algorithm model, in response that the first algorithm model is determined to be better than the second algorithm model; and
generate the evaluation index by inputting the calculation parameters to a reliability model.
18 . The electronic device of claim 13 , wherein the alarm data comprises a first alarm category, a second alarm category, a first time set corresponding to the first alarm category, and a second time set corresponding to the second alarm category, the evaluation index comprises a Mean Time To Failure (MTTF),
the processor is further configured to execute the instructions to:
generate a first MTTF corresponding to the first alarm category based on the first time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model;
generate a second MTTF corresponding to the second alarm category based on the second time set and the first algorithm model, in response that the first algorithm model is better than the second algorithm model; and
generate a MTTF of the at least one equipment based on the first MTTF and the second MTTF.