XUAN Hengnong, ZHANG Runchi, SHI Shengsheng. An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis[J]. Chinese Journal of Electronics, 2016, 25(6): 999-1004. doi: 10.1049/cje.2016.06.035
Citation: XUAN Hengnong, ZHANG Runchi, SHI Shengsheng. An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis[J]. Chinese Journal of Electronics, 2016, 25(6): 999-1004. doi: 10.1049/cje.2016.06.035

An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis

doi: 10.1049/cje.2016.06.035
Funds:  This work is supported by the National Natural Science Foundation of China (No.90718008, No.61133015).
  • Received Date: 2014-10-10
  • Rev Recd Date: 2015-08-14
  • Publish Date: 2016-11-10
  • We propose a new efficient algorithm named Cuckoo search fault diagnosis (CSFD) to solve system-level fault diagnosis problem. KMP algorithm is proposed for initialization based on the K-means partition algorithm; a fitness function is designed according to the equation constraints satisfied by the test model; the binary mapping method is advanced by optimizing existing binary mapping algorithm. Experiments show that KMP algorithm significantly reduces the disparity between the initial solution and the actual solution, and CSFD algorithm improves the efficiency and correctness significantly compared with existing typical swarm intelligence diagnosis algorithm.
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