# Study on Overturn Proof Monitoring System of Mobile Crane
## 3 Performance Evaluation and Field Test  
The mobile crane control program was developed and applied before the actual test and the crane safety program is shown in Figure 6. The system was designed from the ZMP algorithm through Visual Studio 2015 MFC and included the configuration of fixed and variable parameters, the displaying of ZMP results, overturn securing ratio and prediction and warning signals. Moreover, the remaining distance to the felling point, two-stage alarm display and safety display function for each turning angle were added and the maximum lifting load and safety factor was calculated. In order to find the overturn limit of mobile cranes, the felling condition was determined according to the current state of the crane by using the load change applied to the four outriggers supporting the crane. The crane extends the four outriggers to 0-25 m according to the experimental conditions and locates the axle underneath as shown in Figure 7 (a sensor for measuring the load applied to the outrigger) and then lifts the crane by lowering the outrigger. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reaction Forces (kg\({}_{\text{f}}\))** & **Right Front** & **Left Front** & **Right Rear** & **Right Rear** \\ \hline simulation & 7916 & 7961 & 4908 & 4913 \\ actual loads & 8120 & 8290 & 5320 & 5320 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between the simulation result and actual load of reaction force. Figure 6: The mobile crane control program UI. After positioning, the crane performs work according to various experimental conditions from the initial state and simultaneously monitors the reaction force of the outrigger and the state of the crane through the monitoring program as shown in Figure 8.  
The system was developed in a PC environment, connected to two USB ports using serial to USB gender and developed a program using NI Labview. Crane data was programmed to receive 12 data separated by line feed constants. The crane axle was configured to receive and display 4 individual crane data from its own indicator. The displayed value is the sum of the total weight and is displayed on the indicator. Using the monitoring program, we observed the change in reaction force measured in the axle according to the movement of the crane as shown in Figure 9.  
Figure 8: The real time monitoring system of mobile crane. Figure 7: The outrigger axle installation in actual field test. Each outrigger's reaction force result and actual vehicle operation data from attached sensors were equipped with a dual-core CPU or higher to support the appropriate transmission rate of the Android-based OS. The transmission to the control server, 3G or 4G (LTE) communication was used and the Internet of Things (IoT) communication module was adapted to reduce the cost of transmission. Bluetooth 4.0 or higher was used for communication between the terminal and the display, a G-mouse type external GPS module installed inside the terminal was applied to collect location information. Moreover, a temperature sensor and an impact sensor were additionally installed to detect the impact of temperature and impact on the terminal during operation. Lastly, the housing was manufactured based on the theory of mechanism design to satisfying the grade of IP66 (International Protection ratings). The data was stored in accordance with various case experiment scenarios and compared the results with dynamic analysis. The crane measured and stored the amount of reaction force change of the axle crane in real time according to changes in boom length, swing and undulation angle and compared it with dynamic analysis results (moments) and showed a match rate of up to 95%. Figure 10 shows the result of the load changes of the crane according to the boom length. Figure 9: Measuring the reaction force of mobile crane. The data was stored to various experiment scenarios which compared the results via dynamic analysis.