## 5 Results and Discussion
### Data Reconciliation with Gross Errors  
This section is an overview of eight calculation conditions with gross errors. For each working condition, the recognition of sensors with gross errors is shown in Table 9. On the basis of passing the global inspection, the sensors with gross errors under each working condition are well identified, which is based on Equation (16) because the calculated criterion value of \(r\) is greater than 1.96. Compared with the gross errors setting in Table 6, it is found that the two have a good consistency, which also indicates that the data reconciliation model established in this paper is relatively effective in identifying the gross errors of some sensors in the thermal system. The reconciliation results of other sensors in Condition 10 except the sensors with gross errors is shown in Table 10. The deviation of sensors with gross errors is dispersed among all parameters, resulting in an increase in the deviation of some parameters from the design value standard, but the overall deviation level is still low. The highest deviation appears in unknown variables of power and fluctuates around 2%. This result can also show that the gross errors have an obvious influence on the data reconciliation effect, because these errors will not be eliminated, but only dispersed. Even so, it can be seen from the change of uncertainty that the data reconciliation still improves the data accuracy significantly in this case. The distribution of standard deviation in Condition 10 is shown in Figure 8. Due to the addition of gross errors and more random errors, the overall distribution curve has a wider range. However, after data reconciliation, all deviations can be concentrated to the origin. Although the number of variable deviations near the origin is less than before reconciliation due to the effect of large error dispersion, the quality of parameters has been significantly improved. If the gross errors identified can be eliminated in the process of practical application, the reconciliation effect will be better. Figure 7: Distribution of uncertainty in Condition 2. The uncertainty distribution of working condition 10 is shown in Figure 9. There is no significant difference between the distribution trend of uncertainty after adding coarse errors and the previous working conditions. After coordination, the degree of uncertainty reduction is more obvious, the homogeneity is concentrated at the origin and the accuracy of measurement data is improved. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Parameter**} & \multirow{2}{*}{**Design Val.**} & \multicolumn{2}{c}{**Measured De.**} & \multicolumn{2}{c}{**Reconciliated**} & \multirow{2}{*}{**Un.**} & \multirow{2}{*}{**Unit**} \\  & & **Val.** & & **De.** & & & **Val.** & & **De.** & \\ \hline Mass flow of gas & 92.900 & 92.650 & \(-\)0.27\% & 5.00\% & 93.495 & 0.64\% & 2.54\% & kg/s \\ H hot side & 72.690 & 73.416 & 0.10\% & 0.58\% & 73.512 & 1.13\% & 0.46\% & \({}^{\circ}\)C \\ output temperature & 517.600 & 518.318 & 0.14\% & 0.25\% & 517.932 & 0.06\% & 0.12\% & \({}^{\circ}\)C \\ Mass flow of CO\({}_{2}\) in ST1 & 69.890 & 70.056 & 0.24\% & 10.00\% & 70.952 & 1.52\% & 2.56\% & kg/s \\ SC inlet pressure & 8.000 & 8.033 & 0.42\% & 2.00\% & 8.013 & 0.17\% & 1.36\% & MPa \\ SC inlet temperature & 32.000 & 32.086 & 0.27\% & 0.66\% & 32.396 & 1.24\% & 0.18\% & \({}^{\circ}\)C \\ AC power & 40,014 & 39,817 & \(-\)0.49\% & 12.38\% & 39.908 & \(-\)0.26\% & 2.85\% & kW \\ GT power & 70,997 & 71,131 & 0.19\% & 11.21\% & 72,305 & 1.84\% & 2.64\% & kW \\ ST1 power & 9490 & 9549 & 0.63\% & 11.86\% & 9648 & 1.67\% & 2.86\% & kW \\ ST2 power & 6733 & 6789 & 0.84\% & 15.91\% & 6873 & 2.09\% & 2.87\% & kW \\ SC power & 3457 & 3502 & 1.30\% & 12.23\% & 3479 & 0.64\% & 9.47\% & kW \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Reconciliation results of some parameters in Condition 10.