Research Article
Nonlinear Fault Separation for Redundancy Process Variables Based on FNN in MKFDA Subspace
Table 1
Steps designed in this paper.
| Inputs | , , , |
| Step 1 | Initiate and compute , | Step 2 | Select suitable multikernel function | Step 3 | Compute the kernel mean vector between two kinds with
| Step 4 | Compute the kernel scatter matrix of intraclass
| Step 5 | Compute , | Step 6 | Get the optimal solution of (16) | Step 7 | Place the inspected process variable as zero in original samples | Step 8 | Project the new samples into the feature space | Step 9 | Compute the contribution of one variable at one time with FNN in MKFDA | Step 10 | Repeat the above course for the remaining variables |
| Outputs | The distance measure of each original variable is obtained |
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