4.2.2. Experimental Fitting Images

The fitting images of experimental results and real results of interval lower bound (*a*1, *a*2, *a*), interval median ( *m*1, *m*2, *m*) and interval upper bound (*b*1, *b*2, *b*) are listed below. In this paper, the fitting images of the three groups are drawn, respectively, as shown in Figure 11. The results of the three groups were processed by BRB, respectively, and compared with the real value to obtain the error, and finally unified analysis and summary.

**Figure 11.** *Cont*.

**Figure 11.** Fitting diagram right of experimental results and real values.

It can be seen that the results of the three groups of experiments fit well with real data. It could obtain the accuracy of each group through experiments, and then obtain the fluctuation range of experimental accuracy of the case. Then, this paper performed 10 experiments to find out the accuracy and, in this experiment, the accuracy of the three groups was 97.98%, 98.99% and 100.00%, the average accuracy of this experiment is 98.99%. It can be concluded that the accuracy of this experiment fluctuates in the range of 97.98% to 100%. In general, the FFBRB model established in this paper has a good processing effect. The experimental diagnosis results are shown in Figure 11.

4.2.3. Other Comparative Experiments

In this paper, ELM and BP neural networks, as the other two comparison methods of this experiment, are also used in flywheel fault diagnosis. This paper also drew the fitting images of the two control experiments, and it can be seen that the ELM and BP neural network methods are feasible, but still not as accurate as the FFBRB scheme. Among them, the difference between ELM and FFBRB schemes is relatively large, and the difference between BP neural network and FFBRB is not very large.

Two other groups of comparison experiments were conducted in this paper to compare with the FFBRB model method used in this paper, and the experimental results are shown in Figure 12 below.

**Figure 12.** *Cont*.

**Figure 12.** Fitting diagram of experimental results by BP method.

Figure 13 shows the diagnosis results obtained in ELM mode.

**Figure 13.** *Cont*.

**Figure 13.** Fitting diagram of experimental results by ELM method.

In this experiment, the accuracy of 10 groups of data is taken, and the average of their probability is taken as the final result. The floating line chart of the accuracy of these 10 groups is shown in Figure 14.

In the three groups of the BP method, the average accuracy of the experimental fault diagnosis value compared with the real value is 85.90%, 91.30% and 85.50%, respectively. In the three groups of the ELM method, the average accuracy of the experimental fault diagnosis value obtained by us compared with the real value is 54.40%, 63.20% and 65.50%, respectively.

**Figure 14.** Comparison of experimental accuracy of different methods.

In the three groups of the FFBRB method, the average accuracy of the experimental fault diagnosis value obtained by us compared with the real value is 99.7%, 98.18% and 99.39%, respectively. This paper took the total average accuracy of the three groups of the three methods, and after calculation, the average accuracy of the BP method is 87.57%, the ELM method is 61.03%, the FFBRB method is 99.09%.

To facilitate intuitive observation, this paper sorted these data into a table, as shown in Table 7 below:


**Table 7.** Comparison of results of different methods.
