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Traditional diesel engine fault diagnostic technologies have increasingly shown deficiencies and shortcomings. Under this background, this paper adopts the naive Bayesian classifier method which built on the basis of the probability density function to diagnose the fault of diesel engine. Among all the improving approaches of Naive Bayesian classifier, integrated one-dependence estimators present...
Among all the improving approaches of Naïve Bayesian classifier, integrated one-dependence estimators present their advantages both in accuracy and complexity. This paper proposes a new approach to weight the super-parent one dependence estimators. To verify the validity of the proposed method, the experiments are performed using 16 datasets collected by University of California Irvine (UCI) and...
As the shortcomings of BP neural network slow convergence rate, falling into local minimum easily and difficult to determine the number of hidden nodes accurately, the number of hidden nodes, weights and threshold of BP neural network were optimized, using binary and real number hybrid coding based on genetic algorithms with global searching ability. Finally, the method tested with WD615 diesel engine...
This paper indicating to the actual question of a surface-to-air missile system failure diagnosis, researched the fault intelligent diagnosis question through the expert system method. A surface-to-air missile equipment Fault Diagnosis Expert System based on the rules-ratiocination technique is conceived by the notation of equipment, fault knowledge based on the rules-ratiocination technique, and...
Multivariate statistical process monitoring (MSPM) has received increasing attention, which is applied to improve process operations by detecting when abnormal process operations exist and diagnosing the sources of the abnormalities. This paper presents a MSPM application method on grinding processes, including principal component analysis (PCA), fault detection and fault diagnosis using the contributions...
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