# Design and Implementation of Spring Cable Shaping Method Based on Fuzzy Control
## 5 Experimental Test  
In order to verify the superiority of the temperature fuzzy control algorithm of the cable winding rod designed in this paper, a PID algorithm carried out with the cable heating furnace to control the temperature of the cable winding rod compares with the proposed method. PID algorithm is widely used for temperature control in the industrial field [15]. A constant temperature and humidity cable heating furnace adopts a high-precision intelligent instrument as the temperature controller, PT100 as the temperature sensor, and the temperature control range is from \(-50\)\({}^{\circ}\)C to 200 \({}^{\circ}\)C. An intelligent PID control algorithm is adopted and PID parameters are self-tuning in experiment. Taking 120 \({}^{\circ}\)C and 140 \({}^{\circ}\)C as the set values, the temperature control curves are shown in Figure 3. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multirow{2}{*}{\(I\)} & \multicolumn{8}{c}{\(e_{1}\)} \\ \cline{3-8}  & & \(VB\) & \(B\) & \(M\) & \(S\) & \(VS\) & \(Z\) \\ \hline \multirow{4}{*}{\(e_{2}\)} & \(VB\) & \(VB_{(1)}\) & \(VB_{(7)}\) & \(VB_{(13)}\) & \(B_{(19)}\) & \(M_{(25)}\) & \(Z_{(31)}\) \\  & \(B\) & \(VB_{(2)}\) & \(VB_{(8)}\) & \(B_{(14)}\) & \(B_{(20)}\) & \(M_{(26)}\) & \(Z_{(32)}\) \\  & \(M\) & \(VB_{(3)}\) & \(VB_{(9)}\) & \(B_{(15)}\) & \(B_{(21)}\) & \(M_{(27)}\) & \(Z_{(33)}\) \\  & \(S\) & \(B_{(4)}\) & \(B_{(10)}\) & \(B_{(16)}\) & \(M_{(22)}\) & \(S_{(28)}\) & \(Z_{(34)}\) \\  & \(VS\) & \(B_{(5)}\) & \(B_{(11)}\) & \(M_{(17)}\) & \(VS_{(23)}\) & \(VS_{(29)}\) & \(Z_{(35)}\) \\  & \(Z\) & \(VS_{(6)}\) & \(VS_{(12)}\) & \(VS_{(18)}\) & \(Z_{(24)}\) & \(Z_{(30)}\) & \(Z_{(36)}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameter fuzzy rules. The data in Figure 3 is summarized as follows:  
It can be seen from Table 3 that under the condition of no load (helix), the adjustment time of PID control of the oven through the intelligent instrument is about 7-8 times that of the winding rod fuzzy control. Although the final steady state error is little different, the adjustment time is long and the fluctuation in the adjustment process is relatively large. The following experiments are carried out under the condition of load (helix). Select the same type of TPU cable with the same length, and divide it into group A and group B. Place the winding rod of group a spring cable in a small oven, and heat it with wire baking method. Set the heating electrode on the winding rod of group B spring cable, and heat it with current heating method. The test temperature curves are shown in Figures 4 and 5, respectively. In Figure 4, the heating medium temperature of the oven is set at 140 \({}^{\circ}\)C, the temperature of the oven slowly rise, and the temperature of the spring cable gradually rises with the temperature of the oven. Due to the poor thermal conductivity of the air, it takes about 350 s for the cable temperature to rise from room temperature to the process temperature. If the actual production large-scale curing barn is used, the heating time is far more than 350 s. In Figure 5, the winding rod can be heated to 160 \({}^{\circ}\)C after the electric heating medium of winding rod electrified for about 20 s. Since the cable is in close contact with the winding rod, the temperature of the cable rapidly rises, and the cable can be heated to 140 \({}^{\circ}\)C after about 60 s. Based on the fuzzy control algorithm, the current is automatically adjusted, the temperature of the winding rod gradually decreases, the temperature of the cable slowly rises, and finally approaches the temperature of the winding rod. The shaping effect of spring cable is shown in Figures 6 and 7. Figure 3: Comparison of temperature control effect.