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Affected by both of the internal and external factors during work process, the dam monitoring effect variable often generates complex cycles such as jumps, compendium, and re-jumps, which shows a high degree of non-linearity that brings a lot of trouble in the establishment of regular dam safety monitoring forecast model. Drawing on the threshold thought of the threshold autoregressive model, the threshold factor and the threshold value are introduced in the conventional regression model. By making use of the suggested best fitting correlation analysis method to determine the threshold factor and the threshold value, the threshold regression model is established. Application example shows that the method for dam safety monitoring forecast can obtain satisfactory results.

In this study we analyze the signal in measurement system with distributed optical fiber sensors. The display signal is defined by the user not for general custom. The data of for-processing-part are processed regularly, which directly provides results for the user from the monitoring system. These results go into the next step to add environmental parameters, which includes weather, special events and season information. Information fusion and matching operation of the result and environment information enhances the accuracy of hidden hazard early warning.

Based on briefly introducing the works of BOTDR, article studied on dike strain monitoring by using the distributed optical fiber measurement system produced by OMNISENS in Swiss. Builded the dike model, monitored the dike strain changes influenced by seepage and loading, we try to verify the feasibility that the distributed optical fiber measurement system can basically reflect the dike deformation. It can be an important direction for the development of dike strain monitoring.